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165 KiB
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1 line
165 KiB
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Instalacja pakietów"],"metadata":{"id":"ZXsOR6oJOJbd"}},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"8l0hzptKNiZS","executionInfo":{"status":"ok","timestamp":1676655657013,"user_tz":-60,"elapsed":25722,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"e4743567-b234-4fae-8159-c51d9a68b430"},"outputs":[{"output_type":"stream","name":"stdout","text":["Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Collecting transformers\n"," Downloading transformers-4.26.1-py3-none-any.whl (6.3 MB)\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.3/6.3 MB\u001b[0m \u001b[31m42.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hCollecting datasets\n"," Downloading datasets-2.9.0-py3-none-any.whl (462 kB)\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m462.8/462.8 KB\u001b[0m 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sentencepiece"]},{"cell_type":"markdown","source":["# Załadowanie datasetu"],"metadata":{"id":"dhN0rmb5Oi3d"}},{"cell_type":"code","source":["from datasets import load_dataset"],"metadata":{"id":"tnaDkwZ2Pbnn","executionInfo":{"status":"ok","timestamp":1676655657691,"user_tz":-60,"elapsed":683,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}}},"execution_count":2,"outputs":[]},{"cell_type":"code","source":["dataset = load_dataset(\"sms_spam\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":232,"referenced_widgets":["b6eded70136441759cc5ac10b00acb8f","c5f3c896b6534c178ae822c32a8e00b3","fe35cc2de5b840e49d9d9c5fec869656","532adf3b2f7a4b75a095e9455351553c","646379eb229040dcb09aa0f03d6f3f26","5ee0acafd6944686b9ef3dedabed6aef","e3f4a5f8f4864b0d8357aa29d2b8802f","9152a884650a486f9275278678061eec","9e9b5088b6054ba2a48c6b7872a2c383","f222becd734644c4ae631d432e1b3156","510afccfa74748c4bd69a10dc53e3b70","e7db60e680f04318a706fcb1fe7dbcb7","101d73ffbf8c47af9f62103648edc548","5a5500aa9fd84381be7676f570665d7a","76c1dca21a3c4c3c91769c48a4428ba3","cee9b746e101471cb5808e2415091f38","292d1d346d9246f99b87709fac58b0f0","94ddbe64d035427d943606085a697f23","8f9eb5f919144f74856d354642cff880","176ebdce409b49d59423292931d8a5df","a35c33cb3774427f8e739a7b1c948f4e","ea9bb434237643ab8bb4e4d6f884ba67","b1810e9efa944f08ba50be015456287f","76abc09e7e794eef9ffc3081b2ec2da6","2fbff5b358734b579a1b1d471934150d","4a0b0fc9717b4fc6bf5ad887785dec90","af367d23351544f187286a069b469e89","dd56ef64cae84c3f8dcb52b86bfeeede","107cf57f7ba34a7b82a99035098cd60a","d3f4f7df0b8f41b7a11bf9ca7a2c02d1","f0f50dea946240a79adce466c2810c5a","0d06ef4561694b2e8a5c495f55f01320","d8f9577b8ef8418597e3e327ad29e119","97a4213ad47f47aaae8dce4947c541d5","4ae43dc6645b4e7abfd5018b40b6e1cf","1f2721589fd549269dd8c04fb00ac0b1","cfe42f1c148c4507b8bed4eade47d2cd","a91105129f0a4d0daf1f92beee7b696b","ec41724b9add4285bc5d04715505675b","a1ef5bde067c4250b5d5b74ce8b2945d","79810b4bd66442aba12328e39a00e438","5f0c3fbda713440d80ec4d0654b5892d","78e6dfa135804ed785e0a809356c5112","5fe984999000415b8770abe7c6d65bfc","f53b16108c93439d9943b35c28d57988","8a180e9d3cef4d58a5b05509edb39ec4","d97533a9d431471c898cbccb93202900","235bdfd6aee042a587647925981a1fd2","e081d46be72b4d638cf3cc7be14ac651","0154f8d5e1ef4584b2def2e456179951","d2d1b1c19e8e4b18af10bffe9c3a60f5","40b5e64a2d6743cbbb6b3dca004836b9","e9a816019ddc4c34a94059381da2b7b0","e0a987f764274098ace0ce3900e37c5e","e5b7397c80a44e66863276ed6e443dd9","594b168dc8f24064afca0a0353195c35","b641fc8e31514c2e9c9453ba3669575c","c575ee9e9a4846669a70be243ec8a228","48ac88309d404e1cb83e660a8b344ac6","0e48acebc7b04eb2a1b55a0d852ef7b3","edcf26a3835b4db6b3fbfd160b61aa2e","3eaee86b67704d3da78285c7881cff01","167ad19c7da2466db0528865578fda87","5c384622a46e4252a123378d29bc7640","a60f375b3eee415388d742c619966776","39f30b2919dc4ac0b6e3c8d54999a628"]},"id":"cCiAuRqrOkvV","executionInfo":{"status":"ok","timestamp":1676655660188,"user_tz":-60,"elapsed":2500,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"05d2045e-0777-4174-b3b9-d9fe91ea990f"},"execution_count":3,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading builder script: 0%| | 0.00/3.21k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"b6eded70136441759cc5ac10b00acb8f"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading metadata: 0%| | 0.00/1.69k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"e7db60e680f04318a706fcb1fe7dbcb7"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading readme: 0%| | 0.00/4.87k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"b1810e9efa944f08ba50be015456287f"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Downloading and preparing dataset sms_spam/plain_text to /root/.cache/huggingface/datasets/sms_spam/plain_text/1.0.0/53f051d3b5f62d99d61792c91acefe4f1577ad3e4c216fb0ad39e30b9f20019c...\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading data: 0%| | 0.00/203k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"97a4213ad47f47aaae8dce4947c541d5"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Generating train split: 0%| | 0/5574 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f53b16108c93439d9943b35c28d57988"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Dataset sms_spam downloaded and prepared to /root/.cache/huggingface/datasets/sms_spam/plain_text/1.0.0/53f051d3b5f62d99d61792c91acefe4f1577ad3e4c216fb0ad39e30b9f20019c. Subsequent calls will reuse this data.\n"]},{"output_type":"display_data","data":{"text/plain":[" 0%| | 0/1 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"594b168dc8f24064afca0a0353195c35"}},"metadata":{}}]},{"cell_type":"code","source":["dataset['train'][0]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"JKFHPko3OnAV","executionInfo":{"status":"ok","timestamp":1676655660189,"user_tz":-60,"elapsed":5,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"43a7c656-f0bf-4f82-b03e-ebd0b79f377a"},"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'sms': 'Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...\\n',\n"," 'label': 0}"]},"metadata":{},"execution_count":4}]},{"cell_type":"markdown","source":["# Przygotowanie datasetu"],"metadata":{"id":"l140vJrgYxPr"}},{"cell_type":"code","source":["parsed_dataset = []\n","\n","for row in dataset['train']:\n"," text = row['sms'].replace(\"\\n\", \"\")\n"," new_row = {}\n"," new_row['sms'] = text\n"," if row['label'] == 0:\n"," new_row['label'] = \"False\"\n"," else:\n"," new_row['label'] = \"True\"\n"," parsed_dataset.append(new_row)\n","\n","parsed_dataset[0]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"1boUF-YiY3_y","executionInfo":{"status":"ok","timestamp":1676655661173,"user_tz":-60,"elapsed":987,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"add4c55f-079c-4855-d13c-7bde48bedad4"},"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'sms': 'Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...',\n"," 'label': 'False'}"]},"metadata":{},"execution_count":5}]},{"cell_type":"markdown","source":["# Tokenizer FLAN-T5"],"metadata":{"id":"O-J-jBDxPJcn"}},{"cell_type":"code","source":["from transformers import AutoTokenizer"],"metadata":{"id":"P23AYPX1PZ6g","executionInfo":{"status":"ok","timestamp":1676655663313,"user_tz":-60,"elapsed":2143,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}}},"execution_count":6,"outputs":[]},{"cell_type":"code","source":["tokenizer = AutoTokenizer.from_pretrained('google/flan-t5-base')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":145,"referenced_widgets":["964a243415be46aba8b943310ab54d4f","d9ccbf0d26014aa584f3e2d0d0e64a68","5634196dc0bd4424843e7d721d28362a","c72e22a6ab40424286a185ac758a225e","c9ca5157a2e44cbaa02cb0314ac8e8bf","048af3db70184a679800034200d93952","52380821e49d448887f932add9b16584","7cb4cafea7e54229aad82870395b9301","d9cf0cb2ee1d441089e6ac20d1e54a73","78a272e0eac84a749b76b020b224e2c7","2bcc9f1090bb4ecbb47d42520d4d6c74","6a38a48eb5034c049d0fa0dd162fde42","d611b1bef9aa412cbf6dd0becf687668","252e6364186e4e58bba4176dfeaa228b","4ce56b53ad74491786d3a4b82a09c542","aa87ddf3f3534242b76614eceb45dc82","54a0814e93494f0587bd9442442d60e5","94fc372b752744acb1531d8b1f1d02b5","f4291e0fb592452da1534aca02b5b243","6eb57a003ef04f859ee2830509bfbf93","ef1e797b056e450dac1978e5f4efe1f7","452c422624844f0c8110d152a9104c9f","8b43122390244756b58b00a4f9f1c688","17c157997bef447eb088bebf861f9bbe","96a48ca37c2d43fa9dfb4c3c1304853d","ce990df56c0940fc82cf14f707f8e3c7","4c52f383bef64bb8b7a149ad13f2940b","25ec8aec80864a329cf638caa132a817","5b4ae3431a0843158e741f442f113d23","96b40bca89974400804e5e1f5137bd5d","8ef713aee0aa4684850f15b779a4c8d1","d9ee9576b8ef4788ba652a875584afc3","c0ffdbf9221546d09683913904bc2b21","3b408f071d0c400d9997aeeedb3c55bb","b5a3a5676b634e3f9b845ea4107c5904","b4392fe0efc34fad87c768ba499d5d97","4ea08493d1024dd4b26ea6f8729942ef","602780d3231f4f688305e405040f08dd","3852f79010154f9c89278aacf1ce0b60","d96da6f789e74166841bd8f2cab5bfdc","ebf96cf2dcef46faa724639b045a8f3e","28bb6d7812704dc3b1edcd519d78ead7","83f17383616d4ff0b73f0f7fa198d8fb","c11dfd5356d54640ad384937470f2730"]},"id":"q5Jz0E_oPMBr","executionInfo":{"status":"ok","timestamp":1676655665494,"user_tz":-60,"elapsed":2191,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"63846fa5-30f2-43bb-b10f-4a2df75f8f1e"},"execution_count":7,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading (…)okenizer_config.json: 0%| | 0.00/2.54k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"964a243415be46aba8b943310ab54d4f"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)\"spiece.model\";: 0%| | 0.00/792k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6a38a48eb5034c049d0fa0dd162fde42"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)/main/tokenizer.json: 0%| | 0.00/2.42M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"8b43122390244756b58b00a4f9f1c688"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)cial_tokens_map.json: 0%| | 0.00/2.20k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"3b408f071d0c400d9997aeeedb3c55bb"}},"metadata":{}}]},{"cell_type":"code","source":["sms = parsed_dataset[0]['sms']\n","print('Original: ', sms)\n","print('Tokenized: ', tokenizer.tokenize(sms))\n","print('Token IDs: ', tokenizer.convert_tokens_to_ids(tokenizer.tokenize(sms)))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"dfxJQpoePsvI","executionInfo":{"status":"ok","timestamp":1676655665494,"user_tz":-60,"elapsed":15,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"d4da4d86-1f3b-4d6c-bd8a-532230c3539b"},"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["Original: Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...\n","Tokenized: ['▁Go', '▁until', '▁jur', 'ong', '▁point', ',', '▁crazy', '.', '.', '▁Available', '▁only', '▁in', '▁bug', 'is', '▁', 'n', '▁great', '▁world', '▁la', '▁', 'e', '▁buffet', '...', '▁Cine', '▁there', '▁got', '▁', 'a', 'more', '▁wa', 't', '...']\n","Token IDs: [1263, 552, 10081, 2444, 500, 6, 6139, 5, 5, 8144, 163, 16, 8143, 159, 3, 29, 248, 296, 50, 3, 15, 15385, 233, 17270, 132, 530, 3, 9, 3706, 8036, 17, 233]\n"]}]},{"cell_type":"markdown","source":["# Few shot learning"],"metadata":{"id":"UpluhM8cU5Ir"}},{"cell_type":"code","source":["print(parsed_dataset[0]) #0\n","print(parsed_dataset[123]) #1\n","print(parsed_dataset[2000]) #0\n","print(parsed_dataset[3002]) #1"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7uNUkixPU85O","executionInfo":{"status":"ok","timestamp":1676655665495,"user_tz":-60,"elapsed":13,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"6eda01c2-b3ad-4f08-919e-2a6e8b6beb31"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["{'sms': 'Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...', 'label': 'False'}\n","{'sms': 'Todays Voda numbers ending 7548 are selected to receive a $350 award. If you have a match please call 08712300220 quoting claim code 4041 standard rates app', 'label': 'True'}\n","{'sms': \"LMAO where's your fish memory when I need it?\", 'label': 'False'}\n","{'sms': 'This message is free. Welcome to the new & improved Sex & Dogging club! To unsubscribe from this service reply STOP. msgs@150p 18+only', 'label': 'True'}\n"]}]},{"cell_type":"code","source":["non_spam_1 = \"The text message: \" + parsed_dataset[0]['sms'] + \"\\nIs this sms spam? Ans: False\\n\\n\"\n","spam_1 = \"The text message: \" + parsed_dataset[123]['sms'] + \"\\nIs this sms spam? Ans: True\\n\\n\"\n","non_spam_2 = \"The text message: \" + parsed_dataset[2000]['sms'] + \"\\nIs this sms spam? Ans: False\\n\\n\"\n","spam_2 = \"The text message: \" + parsed_dataset[3002]['sms'] + \"\\nIs this sms spam? Ans: True\\n\\n\"\n","\n","few_shot_prefix = non_spam_1 + spam_1 + non_spam_2 + spam_2 + \"The text message: \"\n","print(few_shot_prefix)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lj0issBznZfK","executionInfo":{"status":"ok","timestamp":1676655665495,"user_tz":-60,"elapsed":11,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"84d05249-8a44-4217-d08e-d4aa86a73063"},"execution_count":10,"outputs":[{"output_type":"stream","name":"stdout","text":["The text message: Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...\n","Is this sms spam? Ans: False\n","\n","The text message: Todays Voda numbers ending 7548 are selected to receive a $350 award. If you have a match please call 08712300220 quoting claim code 4041 standard rates app\n","Is this sms spam? Ans: True\n","\n","The text message: LMAO where's your fish memory when I need it?\n","Is this sms spam? Ans: False\n","\n","The text message: This message is free. Welcome to the new & improved Sex & Dogging club! To unsubscribe from this service reply STOP. msgs@150p 18+only\n","Is this sms spam? Ans: True\n","\n","The text message: \n"]}]},{"cell_type":"markdown","source":["# Load FLAN-T5 model"],"metadata":{"id":"okTx_ynMV0rH"}},{"cell_type":"code","source":["from transformers import AutoModelForSeq2SeqLM"],"metadata":{"id":"Eu-7Eed8WgN0","executionInfo":{"status":"ok","timestamp":1676655665496,"user_tz":-60,"elapsed":10,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}}},"execution_count":11,"outputs":[]},{"cell_type":"code","source":["model = AutoModelForSeq2SeqLM.from_pretrained('google/flan-t5-base')\n","\n","model.cuda()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["1d866806e15243a2a6b9e2896ab4b080","04e36c5f9ad54eb6a65d67a7f3fdc1fe","fe942481952145bca2b065fdffc57a6e","10fbb2a9d59f4ff7b93a861bd23ec11b","50247834284941eea259a5459f873d78","e39fa7c808b74eca8d36cb520a88f9e9","af4350eb2fc448b4a1b5622bdae46f2b","5f0f327f5ae840539f5965141a2699b8","9bac8da88a2f42cc8d78d614b4ed8c4b","35c19f99eb06497d9de7cbf22bc3e470","db017986b1de4a60b4a8580520bda5b1","085045127f87427db73a60ef1e327611","53ad0ff2b0ab46b9bac26bb2151f7a15","ff0432bc9c734568a3f3dd05aa7120ad","ae9a1c87abfe47bb9910952d21816dd4","631fb86b84694e71b4e07ed87814ecbf","9ea753414ae9483c897b5adfb20af8d4","bdde8de9755c44d6962b548c37d9c927","a1085e971cf24f19b8e7f9f2483bb121","7b0f22568b804917822961916976b5a2","22f612f85b3e405c9d7a8b6563bd41fb","b744c050c4484789894483a0c55275a5","af73747a621844c7a0560a1527a76c9d","7288441ae4d64cc89a674627c154512d","91d82b64e46a4a6b8d706e12d6148aae","89241d98f79640b39d443848c6e58007","a983652b826543048fb2ef76e9411246","348e436208d64851a731e120efd00038","4df5440f92674ad09462e65c90b3ddb5","f7c349857ab24d51bcc5e718ec9812aa","9ae246e32e3544d19cf057573ff02b30","8897f4dfcbe94bf99e0af6222abe0298","82538e6c3518482aa1ad2357685ce2f6"]},"id":"JKv9O8kfV2zZ","executionInfo":{"status":"ok","timestamp":1676655691072,"user_tz":-60,"elapsed":25585,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"171d7691-dd21-4661-a11f-d1a7fe31cc5d"},"execution_count":12,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading (…)lve/main/config.json: 0%| | 0.00/1.40k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"1d866806e15243a2a6b9e2896ab4b080"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)\"pytorch_model.bin\";: 0%| | 0.00/990M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"085045127f87427db73a60ef1e327611"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)neration_config.json: 0%| | 0.00/147 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"af73747a621844c7a0560a1527a76c9d"}},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["T5ForConditionalGeneration(\n"," (shared): Embedding(32128, 768)\n"," (encoder): T5Stack(\n"," (embed_tokens): Embedding(32128, 768)\n"," (block): ModuleList(\n"," (0): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," (relative_attention_bias): Embedding(32, 12)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (1): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (2): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (3): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (4): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (5): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (6): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (7): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (8): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (9): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (10): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (11): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," )\n"," (final_layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (decoder): T5Stack(\n"," (embed_tokens): Embedding(32128, 768)\n"," (block): ModuleList(\n"," (0): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," (relative_attention_bias): Embedding(32, 12)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (1): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (2): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (3): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (4): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (5): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (6): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (7): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (8): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (9): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (10): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," (11): T5Block(\n"," (layer): ModuleList(\n"," (0): T5LayerSelfAttention(\n"," (SelfAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (1): T5LayerCrossAttention(\n"," (EncDecAttention): T5Attention(\n"," (q): Linear(in_features=768, out_features=768, bias=False)\n"," (k): Linear(in_features=768, out_features=768, bias=False)\n"," (v): Linear(in_features=768, out_features=768, bias=False)\n"," (o): Linear(in_features=768, out_features=768, bias=False)\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (2): T5LayerFF(\n"," (DenseReluDense): T5DenseGatedActDense(\n"," (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n"," (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n"," (wo): Linear(in_features=2048, out_features=768, bias=False)\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," (act): NewGELUActivation()\n"," )\n"," (layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," )\n"," )\n"," )\n"," (final_layer_norm): T5LayerNorm()\n"," (dropout): Dropout(p=0.1, inplace=False)\n"," )\n"," (lm_head): Linear(in_features=768, out_features=32128, bias=False)\n",")"]},"metadata":{},"execution_count":12}]},{"cell_type":"markdown","source":["# Helper functions"],"metadata":{"id":"F_SDAwxoawDy"}},{"cell_type":"code","source":["import torch"],"metadata":{"id":"rdWMg_KJZEZH","executionInfo":{"status":"ok","timestamp":1676655691073,"user_tz":-60,"elapsed":8,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}}},"execution_count":13,"outputs":[]},{"cell_type":"code","source":["def calculate_accuracy(preds, target):\n"," results_ok = 0.0\n"," results_false = 0.0\n","\n"," for idx, pred in enumerate(preds):\n"," if pred == target[idx]:\n"," results_ok += 1.0\n"," else:\n"," results_false += 1.0\n","\n"," return results_ok / (results_ok + results_false)"],"metadata":{"id":"FzUi8908ax61","executionInfo":{"status":"ok","timestamp":1676655691074,"user_tz":-60,"elapsed":8,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}}},"execution_count":14,"outputs":[]},{"cell_type":"code","source":["if torch.cuda.is_available(): \n"," device = torch.device(\"cuda\")\n","\n"," print('There are %d GPU(s) available.' % torch.cuda.device_count())\n"," print('We will use the GPU:', torch.cuda.get_device_name(0))\n","\n","else:\n"," print('No GPU available, using the CPU instead.')\n"," device = torch.device(\"cpu\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"86i7iRmtW-6L","executionInfo":{"status":"ok","timestamp":1676655691074,"user_tz":-60,"elapsed":8,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"d0f160f4-a67c-4269-d22c-db44fe8c9457"},"execution_count":15,"outputs":[{"output_type":"stream","name":"stdout","text":["There are 1 GPU(s) available.\n","We will use the GPU: Tesla T4\n"]}]},{"cell_type":"markdown","source":["# Predykcja"],"metadata":{"id":"H_YI3bS3VHQE"}},{"cell_type":"code","source":["parsed_dataset = parsed_dataset[1:123] + parsed_dataset[124:2000] + parsed_dataset[2001:3002] + parsed_dataset[3003:]\n","predictions = []\n","expected = []\n","\n","for row in parsed_dataset:\n"," input_text = few_shot_prefix + row['sms'] + \"\\nIs this sms spam? Ans: \"\n"," input_ids = tokenizer(input_text, return_tensors=\"pt\").input_ids.to(device)\n","\n"," generated_ids = model.generate(input_ids, do_sample=True, temperature=0.9, max_length=300)\n"," generated_text = tokenizer.decode(generated_ids[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)\n"," \n"," predictions.append(generated_text)\n"," expected.append(row['label'])\n","\n","acc = calculate_accuracy(predictions, expected)\n","print(acc)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vunLGuBGVGmh","executionInfo":{"status":"ok","timestamp":1676656276714,"user_tz":-60,"elapsed":384554,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"98047a20-86db-4d62-bd76-a8daaca995d6"},"execution_count":17,"outputs":[{"output_type":"stream","name":"stdout","text":["0.28404599353215954\n"]}]},{"cell_type":"code","source":["print(\"Sample prediction: {}, expected: {}\".format(predictions[101], expected[101]))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"20WbYZmLaDl7","executionInfo":{"status":"ok","timestamp":1676656326544,"user_tz":-60,"elapsed":235,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"70a99496-a105-4d1f-f713-c3c08aa48b1a"},"execution_count":18,"outputs":[{"output_type":"stream","name":"stdout","text":["Sample prediction: Yes, expected: False\n"]}]},{"cell_type":"markdown","source":["# MCC Score"],"metadata":{"id":"dLYc9WXz_B1o"}},{"cell_type":"code","source":["from sklearn.metrics import matthews_corrcoef\n","\n","print('Calculating Matthews Corr. Coef. for each batch...')\n","matthews = matthews_corrcoef(expected, predictions) \n","print('Total MCC: %.3f' % matthews)"],"metadata":{"id":"hPEPpXXX_DXR","executionInfo":{"status":"ok","timestamp":1676656330154,"user_tz":-60,"elapsed":787,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"c970bf13-032f-4912-a83c-91276ca70465"},"execution_count":19,"outputs":[{"output_type":"stream","name":"stdout","text":["Calculating Matthews Corr. Coef. for each batch...\n","Total MCC: 0.006\n"]}]},{"cell_type":"markdown","source":["# Save model"],"metadata":{"id":"GPhCp068_Iwq"}},{"cell_type":"code","source":["from google.colab import drive\n","\n","drive.mount('/content/gdrive/', force_remount=True)\n","\n","output_dir = '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/Ver_5_FLAN-T5_Model'\n","print(\"Saving model to %s\" % output_dir)\n","\n","model_to_save = model.module if hasattr(model, 'module') else model\n","model_to_save.save_pretrained(output_dir)\n","tokenizer.save_pretrained(output_dir)"],"metadata":{"id":"avafCMoS_KDF","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1676656352075,"user_tz":-60,"elapsed":19468,"user":{"displayName":"Mike3 Studia3","userId":"17253749482577755833"}},"outputId":"649fa4ed-c4cf-44bd-9137-013045151068"},"execution_count":20,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/gdrive/\n","Saving model to /content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/Ver_5_FLAN-T5_Model\n"]},{"output_type":"execute_result","data":{"text/plain":["('/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/Ver_5_FLAN-T5_Model/tokenizer_config.json',\n"," '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/Ver_5_FLAN-T5_Model/special_tokens_map.json',\n"," '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/Ver_5_FLAN-T5_Model/spiece.model',\n"," '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/Ver_5_FLAN-T5_Model/added_tokens.json',\n"," '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/Ver_5_FLAN-T5_Model/tokenizer.json')"]},"metadata":{},"execution_count":20}]},{"cell_type":"markdown","source":["# Bibliografia\n","- https://huggingface.co/docs/transformers/main/en/model_doc/flan-t5\n","- https://mccormickml.com/2019/07/22/BERT-fine-tuning/#a1-saving--loading-fine-tuned-model\n","- https://huggingface.co/docs/transformers/model_doc/t5#training"],"metadata":{"id":"wHzm2_nDA6i-"}}]} |