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"colab": { "base_uri": "https://localhost:8080/" }, "id": "u29i-U30zRjY", "outputId": "ac62ad4d-2a0d-4fe7-f784-08c88284c6ee" }, "execution_count": 1, "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 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 \u001b[31m10.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hCollecting 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[31m62.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: torch in /usr/local/lib/python3.8/dist-packages (1.13.1+cu116)\n", "Requirement already satisfied: scikit-learn in 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(loaded_data['train'], data_train, None),\n", " (loaded_data['test'], data_valid, None),\n", "]:\n", " for i, data in enumerate(source_data):\n", " if max_size is not None and i >= max_size:\n", " break\n", " data_line = {\n", " 'label': int(data['label']),\n", " 'text': data['text'],\n", " }\n", " dataset.append(data_line)\n", "\n", "print(f'Train: {len(data_train):6d}')\n", "print(f'Valid: {len(data_valid):6d}')\n", "\n", "data_class_1, data_class_2 = [], []\n", "\n", "for data in data_valid:\n", " label = data['label']\n", " if label == 0:\n", " data_class_1.append(data)\n", " elif label == 1:\n", " data_class_2.append(data)\n", "\n", "print(f'Label 1: {len(data_class_1):6d}')\n", "print(f'Label 2: {len(data_class_2):6d}')\n", "\n", "size_half_class_1 = int(len(data_class_1) / 2)\n", "size_half_class_2 = int(len(data_class_2) / 2)\n", "\n", "data_valid = data_class_1[:size_half_class_1] + data_class_2[:size_half_class_2]\n", "data_test = data_class_1[size_half_class_1:] + data_class_2[size_half_class_2:]\n", "\n", "print(f'Valid: {len(data_valid):6d}')\n", "print(f'Test : {len(data_test):6d}')\n", "\n", "MAP_LABEL_TRANSLATION = {\n", " 0: 'sadness',\n", " 1: 'joy',\n", " 2: 'love',\n", " 3: 'anger',\n", " 4: 'fear',\n", " 5: 'surprise',\n", "}\n", "\n", "def save_as_translations(original_save_path: Path, data_to_save: List[Dict]) -> None:\n", " file_name = 's2s-' + original_save_path.name\n", " file_path = original_save_path.parent / file_name\n", "\n", " print(f'Saving into: {file_path}')\n", " with open(file_path, 'wt') as f_write:\n", " for data_line in data_to_save:\n", " label = data_line['label']\n", " new_label = MAP_LABEL_TRANSLATION[label]\n", " data_line['label'] = new_label\n", " data_line_str = json.dumps(data_line)\n", " f_write.write(f'{data_line_str}\\n')\n", "\n", "for file_path, data_to_save in [(train_path, data_train), (valid_path, data_valid), (test_path, data_test)]:\n", " print(f'Saving into: {file_path}')\n", " with open(file_path, 'wt') as f_write:\n", " for data_line in data_to_save:\n", " data_line_str = json.dumps(data_line)\n", " f_write.write(f'{data_line_str}\\n')\n", " \n", " save_as_translations(file_path, data_to_save)\n", "\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 919, "referenced_widgets": [ "44fd8a6a906443ecbeb69eed3a45c627", "c497031e66574ad0b8b37b185eb29df8", "525732f440d24c03852f9d545e5adbe3", "dab6b534d01043a59b03e19617b2851c", "b40fe391599e4d5fb50a3010bf5a9bd1", "ccdb31dfc2354799b2a0a608731766ff", "406014194c584707826e1249517a92e6", "43d7ade9614c4ad4a721dc64c0366ef8", "651c39733dfd4f18b6f289ba29522bf3", "15b61a47225645fa869cf3cf0f07500d", "8d90dd7fd72a47f38b09ea3a8ffceb09", "9fd2770b475743c1870d4031640268e9", "11be88b31ecb4560ae334d2d4dae01cd", "3d01327fc76b4746b182ca9010133f84", "2681a7fb24bd4347a6e04f6b45293dcc", "8b6422bd938443fdacd8c379e5b548a9", "6e5b96496cd347119af17b14c7fabf58", "f3ecf0f28aa94547921b82291a5535c9", "d8cee759a9744b7e9604384884d8981a", "8213eee944ad43d5a5d0ada0bcaab787", "9bad918205eb4a11934c94292bc489fb", "49ae1883f30941749c4da48249dfdaf4", "386213884eb44d2696a634a584d26eb4", "2f1960dda4994becafad08c1da9d4f9b", "34278cebc12642abb0d39f919575c439", "ab0ec27e7d724161b9bf99a4722e7240", "b6ca46763e474e92907bf0ff778af187", "1806184e8b414fa78211d659077db9f0", "a7c81a606ccf42b89c34a73961b4f5e8", "c2b464c87d2d4d70b5ed0f4cd5c803b1", "4f9b2821339d4add86863e3c6e92aba9", "0776200fdbc04b0da45e50c5d7287e07", "693ac6eecbd046ae931edba2355b4640", "14440bce951547878adf0c7400ed15ad", "eb4ef2280f924b668e3ee3f052d6f7d0", "5a9338583486433aab01abe2483aefb8", "a9e2f6cbf28d453d85f8b7a199eb2cf3", "495f422bfd2b4c1987c69dc00c701c79", "3a990e7fd9f640d09234d09a2ff499d7", "0563f4ab6f84451d84dd67d7b2285be0", "51c62ecdef234c9dae794b306711335a", "f3ff5c22537c4496b8863f12bc9a0d80", "bd1c6d7f61cb4490af676183394be9d6", "693a1713772341aea22435fb431fe5a1", "74be083418f442b1bf7bbde06545ef12", "302e11263fee4d799111074d61a9a233", "df97d4a3494043cf8251d1e882e3268b", "7b397f49fb2a403287eadb0da111d898", "f6fed0c831fb4b9d9d03f3e2b9a6bb87", "d4012b7ccbde46f983cfab3def476fce", "25a57051b2374923b5014b8ebb909ba7", "fbfd09183a0244e68f035263601c51a2", "5cab6b09a63c492ca1530d120679ab48", "1f417fd93b234544adc483c97108a2a5", "dc8a8aa5456b4b45bca4e7834d1fd46c", "cce835f54cc643a0af12cbc5d356c5ee", "71e5a44b26364b84a3729a308b59ee32", "89141b913f414e1388852c0b22fb44c4", "88efb1303f274a5abfcf97610799c51d", "5b8a0a1f096d4a3ca16414d85e05f78c", "8dc33290fa704494b093a95e9f343eaf", "0e7116f299404a22a77ffd13f8fe55d0", "5e791b95c253475792dbc74d22ab0a42", "4f161aeb91e846d1b662f98b92b12a77", "f819da692f47430b8b123c3a84ee0649", "c8593a6f7ecf4a709a9e4188160eb2d4", "3913310317fe4e36bc5271dffa33680e", "6ff96fd4a83e43ea9a5525b425dcb363", "58361d8c6ada485c916d95ffa71a6ece", "f65324f9d9134fb5ae0527c5e2b9e240", "34037231aefb4b209a7dc754686de8e2", "9101c52578b84efca6a849f382efa354", "7f23c9bb679f465d9b8d8a6ce62d9e8a", "de7344a72f234b51ac94d09fc3a5206e", "336f31136fbe49c4b54039b185b02cb0", "7e981332bf924b6790a79bbf85a36e4a", "8263c8b0dcc24f2480673433e4dbc045", "11c2741547654e83b823ed6eec22987a", "c5cd8f2b3fd14508868844c29847dcf3", "f780f939655644618a16f49b6e1123a5", "bf8e27b941b24824811f601cb2d2ef34", "7289597f3c764321b06f19c3ac09038e", "5c050bf1d67f4e58be5083d3788faece", "b32f594b6ba2416f9095d06ac17992cf", "ffe1a65026f444c0a61483ac40eed0d9", "7dc2b971cdce4407991b64a8b7f6c61b", "125e8818ef7c40bf8da82960a973521d", "c86bbf3e606642be9132d99581a910b2", "d3de3065fbb1489a97164ff77773fc6c", "8d06308f999348ef819170a6c48fef29", "5c713b87638d4ee0acd859510ea3e268", "7c351dde4b044e54b8d427394a415e82", "a9552cf61d9f48ae995c588b6b8bde2c", "592adc079c5b42ae83e1fbe1a712805e", "2b4edf08b9f84c5d956436345fad3874", "c84c9601a4b84a118b00c4f85097999b", "7af79791e0b242cd8f85be6840cd9806", "f6256de35d78420a8a01f31ae02bf387", "e0f14d25197149e5969551d181611379", "cfed5de5dc4d4b1793292d16f1369ae3", "ac072b528e9845119a64140ec5c834cf", "8ab9fd20cf4c450dbf5d8bd58fb052ef", "1c39b463926441e79951e66a990d904a", "2d081985e2f74a8ba474101c9991ec4d", "984cd11cfccd4f908292da24d13721ab", "bc28539ef3cb478895162f2e0ac2da46", "8fa3362b7cc74b54bf03be2f028bdec3", "b92a751acaf94b91bea3575555a9b993", "9177954b7e4e4ddbb2775d5371f7f065", "9fb3836adcb1437890f3fb66f752a00a", "06b3f3507a244a70b1ab7c202230b0a4", "3a618fd9060b41d7b6572f4a0932774e", "a622e586448c4ee391c2e57306854eba", "5712711ad4f2426b8a2c533758746e0b", "df6d2e0eaccc4ebcb69fc59da1f8c140", "82517b81dfd846feb71779c3b7a2f308", "2fe49accbd7147ecab1bff77f8869524", "140459cf3400418b8ce91eb4c8d73855", "98952e8528ba46798fbeafa4eb0645f2", "bcf7deac11eb41f0946a1bf360d93e72", "79d68c2bd8b0446991f6a23bb0f092f5", "565253faa71a47db9cdb816a42a79012", "3c680019d0bb40a09b1176141cf2c089", "8c7935fd22884b2892fd84a3c2faa81d", "28ba701f69354634ae0f095cacf703c4", "57026255a6c248ddb89a4dae061179a0", "937495c8ef5a428dafa26abca7336d56", "a0ec6f9b3d8f4b82a948c2eb04f230ff", "31a92d72c53443b5918b6fe4b523a15b", "cc11d2cd77094d74a026329df8bdf07f", "41295d2ec7514b6ba408ffce031f268d", "aa51876a7d9e4ac590ed6f2d620a1fed" ] }, "id": "bcR4tWQl0rqt", "outputId": "d6a86587-a559-4ab8-9e99-2b9dfe509660" }, "execution_count": 3, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading builder script: 0%| | 0.00/3.97k [00:00 data/train-5k.json\n", "!tail -n 2500 data/train.json >> data/train-5k.json\n", "!wc -l data/train-5k.json" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "pRmHIvyB0fZe", "outputId": "ff46a0cb-883a-43c0-b8ec-013a857c745d" }, "execution_count": 4, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "7000 data/train-5k.json\n" ] } ] }, { "cell_type": "code", "source": [ "from pathlib import Path\n", "\n", "for file_name in [\"train\", \"valid\", \"test\", \"s2s-train\", \"s2s-valid\", \"s2s-test\"]:\n", " print(f\"=== {file_name} ===\")\n", " all_text = Path(f\"data/{file_name}.json\").read_text().split('\\n')\n", " text = all_text[:2500] + all_text[-2500:]\n", " Path(f\"data/{file_name}-5k.json\").write_text(\"\\n\".join(text))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "rFa6ijdx2L28", "outputId": "a33255aa-d70e-420f-9df8-abe60c3a1929" }, "execution_count": 5, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "=== train ===\n", "=== valid ===\n", "=== test ===\n", "=== s2s-train ===\n", "=== s2s-valid ===\n", "=== s2s-test ===\n" ] } ] }, { "cell_type": "code", "source": [ "import os\n", "\n", "os.environ['TOKENIZERS_PARALLELISM'] = 'true'" ], "metadata": { "id": "8opbDvBv3ZlK" }, "execution_count": 6, "outputs": [] }, { "cell_type": "code", "source": [], "metadata": { "id": "pxuxjHt8P57X" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!python run_glue.py \\\n", "--cache_dir .cache_training \\\n", "--model_name_or_path gpt2 \\\n", "--custom_model gpt2_hidden \\\n", "--freeze_weights \\\n", "--train_file data/s2s-train.json \\\n", "--validation_file data/s2s-valid.json \\\n", "--test_file data/s2s-test.json \\\n", "--per_device_train_batch_size 24 \\\n", "--per_device_eval_batch_size 24 \\\n", "--do_train \\\n", "--do_eval \\\n", "--do_predict \\\n", "--max_seq_length 128 \\\n", "--learning_rate 2e-5 \\\n", "--num_train_epochs 5 \\\n", "--output_dir out/imdb-5k/gpt2" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "XkkeRPG_z3Jc", "outputId": "db3794a5-563b-44f1-ceff-1a487661a36f" }, "execution_count": 7, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "2023-02-12 20:36:36.029528: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n", "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", "2023-02-12 20:36:36.925834: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib64-nvidia\n", "2023-02-12 20:36:36.925931: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib64-nvidia\n", "2023-02-12 20:36:36.925949: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n", "WARNING:__main__:Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", "INFO:__main__:Training/evaluation parameters TrainingArguments(\n", "_n_gpu=1,\n", "adafactor=False,\n", "adam_beta1=0.9,\n", "adam_beta2=0.999,\n", "adam_epsilon=1e-08,\n", "auto_find_batch_size=False,\n", "bf16=False,\n", "bf16_full_eval=False,\n", "data_seed=None,\n", "dataloader_drop_last=False,\n", "dataloader_num_workers=0,\n", "dataloader_pin_memory=True,\n", "ddp_bucket_cap_mb=None,\n", "ddp_find_unused_parameters=None,\n", "ddp_timeout=1800,\n", "debug=[],\n", "deepspeed=None,\n", "disable_tqdm=False,\n", "do_eval=True,\n", "do_predict=True,\n", "do_train=True,\n", "eval_accumulation_steps=None,\n", "eval_delay=0,\n", "eval_steps=None,\n", "evaluation_strategy=no,\n", "fp16=False,\n", "fp16_backend=auto,\n", "fp16_full_eval=False,\n", "fp16_opt_level=O1,\n", "fsdp=[],\n", "fsdp_min_num_params=0,\n", "fsdp_transformer_layer_cls_to_wrap=None,\n", "full_determinism=False,\n", "gradient_accumulation_steps=1,\n", "gradient_checkpointing=False,\n", "greater_is_better=None,\n", "group_by_length=False,\n", "half_precision_backend=auto,\n", "hub_model_id=None,\n", "hub_private_repo=False,\n", "hub_strategy=every_save,\n", "hub_token=,\n", "ignore_data_skip=False,\n", "include_inputs_for_metrics=False,\n", "jit_mode_eval=False,\n", "label_names=None,\n", "label_smoothing_factor=0.0,\n", "learning_rate=2e-05,\n", "length_column_name=length,\n", "load_best_model_at_end=False,\n", "local_rank=-1,\n", "log_level=passive,\n", "log_level_replica=passive,\n", "log_on_each_node=True,\n", "logging_dir=out/imdb-5k/gpt2/runs/Feb12_20-36-39_64266b139b25,\n", "logging_first_step=False,\n", "logging_nan_inf_filter=True,\n", "logging_steps=500,\n", "logging_strategy=steps,\n", "lr_scheduler_type=linear,\n", "max_grad_norm=1.0,\n", "max_steps=-1,\n", "metric_for_best_model=None,\n", "mp_parameters=,\n", "no_cuda=False,\n", "num_train_epochs=5.0,\n", "optim=adamw_hf,\n", "optim_args=None,\n", "output_dir=out/imdb-5k/gpt2,\n", "overwrite_output_dir=False,\n", "past_index=-1,\n", "per_device_eval_batch_size=24,\n", "per_device_train_batch_size=24,\n", "prediction_loss_only=False,\n", "push_to_hub=False,\n", "push_to_hub_model_id=None,\n", "push_to_hub_organization=None,\n", "push_to_hub_token=,\n", "ray_scope=last,\n", "remove_unused_columns=True,\n", "report_to=['tensorboard'],\n", "resume_from_checkpoint=None,\n", "run_name=out/imdb-5k/gpt2,\n", "save_on_each_node=False,\n", "save_steps=500,\n", "save_strategy=steps,\n", "save_total_limit=None,\n", "seed=42,\n", "sharded_ddp=[],\n", "skip_memory_metrics=True,\n", "tf32=None,\n", "torch_compile=False,\n", "torch_compile_backend=None,\n", "torch_compile_mode=None,\n", "torchdynamo=None,\n", "tpu_metrics_debug=False,\n", "tpu_num_cores=None,\n", "use_ipex=False,\n", "use_legacy_prediction_loop=False,\n", "use_mps_device=False,\n", "warmup_ratio=0.0,\n", "warmup_steps=0,\n", "weight_decay=0.0,\n", "xpu_backend=None,\n", ")\n", "INFO:__main__:load a local file for train: data/s2s-train.json\n", "INFO:__main__:load a local file for validation: data/s2s-valid.json\n", "INFO:__main__:load a local file for test: data/s2s-test.json\n", "WARNING:datasets.builder:Using custom data configuration default-2f4908162fef247b\n", "INFO:datasets.info:Loading Dataset Infos from /usr/local/lib/python3.8/dist-packages/datasets/packaged_modules/json\n", "INFO:datasets.builder:Generating dataset json (/content/.cache_training/json/default-2f4908162fef247b/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51)\n", "Downloading and preparing dataset json/default to /content/.cache_training/json/default-2f4908162fef247b/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51...\n", "Downloading data files: 100% 3/3 [00:00<00:00, 12075.73it/s]\n", "INFO:datasets.download.download_manager:Downloading took 0.0 min\n", "INFO:datasets.download.download_manager:Checksum Computation took 0.0 min\n", "Extracting data files: 100% 3/3 [00:00<00:00, 2299.51it/s]\n", "INFO:datasets.utils.info_utils:Unable to verify checksums.\n", "INFO:datasets.builder:Generating train split\n", "INFO:datasets.builder:Generating validation split\n", "INFO:datasets.builder:Generating test split\n", "INFO:datasets.utils.info_utils:Unable to verify splits sizes.\n", "Dataset json downloaded and prepared to /content/.cache_training/json/default-2f4908162fef247b/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51. Subsequent calls will reuse this data.\n", "100% 3/3 [00:00<00:00, 1048.23it/s]\n", "Downloading (…)lve/main/config.json: 100% 665/665 [00:00<00:00, 121kB/s]\n", "[INFO|configuration_utils.py:660] 2023-02-12 20:36:43,514 >> loading configuration file config.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/config.json\n", "[INFO|configuration_utils.py:712] 2023-02-12 20:36:43,515 >> Model config GPT2Config {\n", " \"_name_or_path\": \"gpt2\",\n", " \"activation_function\": \"gelu_new\",\n", " \"architectures\": [\n", " \"GPT2LMHeadModel\"\n", " ],\n", " \"attn_pdrop\": 0.1,\n", " \"bos_token_id\": 50256,\n", " \"embd_pdrop\": 0.1,\n", " \"eos_token_id\": 50256,\n", " \"id2label\": {\n", " \"0\": \"LABEL_0\",\n", " \"1\": \"LABEL_1\",\n", " \"2\": \"LABEL_2\",\n", " \"3\": \"LABEL_3\",\n", " \"4\": \"LABEL_4\",\n", " \"5\": \"LABEL_5\"\n", " },\n", " \"initializer_range\": 0.02,\n", " \"label2id\": {\n", " \"LABEL_0\": 0,\n", " \"LABEL_1\": 1,\n", " \"LABEL_2\": 2,\n", " \"LABEL_3\": 3,\n", " \"LABEL_4\": 4,\n", " \"LABEL_5\": 5\n", " },\n", " \"layer_norm_epsilon\": 1e-05,\n", " \"model_type\": \"gpt2\",\n", " \"n_ctx\": 1024,\n", " \"n_embd\": 768,\n", " \"n_head\": 12,\n", " \"n_inner\": null,\n", " \"n_layer\": 12,\n", " \"n_positions\": 1024,\n", " \"reorder_and_upcast_attn\": false,\n", " \"resid_pdrop\": 0.1,\n", " \"scale_attn_by_inverse_layer_idx\": false,\n", " \"scale_attn_weights\": true,\n", " \"summary_activation\": null,\n", " \"summary_first_dropout\": 0.1,\n", " \"summary_proj_to_labels\": true,\n", " \"summary_type\": \"cls_index\",\n", " \"summary_use_proj\": true,\n", " \"task_specific_params\": {\n", " \"text-generation\": {\n", " \"do_sample\": true,\n", " \"max_length\": 50\n", " }\n", " },\n", " \"transformers_version\": \"4.26.1\",\n", " \"use_cache\": true,\n", " \"vocab_size\": 50257\n", "}\n", "\n", "[INFO|tokenization_auto.py:458] 2023-02-12 20:36:44,424 >> Could not locate the tokenizer configuration file, will try to use the model config instead.\n", "[INFO|configuration_utils.py:660] 2023-02-12 20:36:45,322 >> loading configuration file config.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/config.json\n", "[INFO|configuration_utils.py:712] 2023-02-12 20:36:45,323 >> Model config GPT2Config {\n", " \"_name_or_path\": \"gpt2\",\n", " \"activation_function\": \"gelu_new\",\n", " \"architectures\": [\n", " \"GPT2LMHeadModel\"\n", " ],\n", " \"attn_pdrop\": 0.1,\n", " \"bos_token_id\": 50256,\n", " \"embd_pdrop\": 0.1,\n", " \"eos_token_id\": 50256,\n", " \"initializer_range\": 0.02,\n", " \"layer_norm_epsilon\": 1e-05,\n", " \"model_type\": \"gpt2\",\n", " \"n_ctx\": 1024,\n", " \"n_embd\": 768,\n", " \"n_head\": 12,\n", " \"n_inner\": null,\n", " \"n_layer\": 12,\n", " \"n_positions\": 1024,\n", " \"reorder_and_upcast_attn\": false,\n", " \"resid_pdrop\": 0.1,\n", " \"scale_attn_by_inverse_layer_idx\": false,\n", " \"scale_attn_weights\": true,\n", " \"summary_activation\": null,\n", " \"summary_first_dropout\": 0.1,\n", " \"summary_proj_to_labels\": true,\n", " \"summary_type\": \"cls_index\",\n", " \"summary_use_proj\": true,\n", " \"task_specific_params\": {\n", " \"text-generation\": {\n", " \"do_sample\": true,\n", " \"max_length\": 50\n", " }\n", " },\n", " \"transformers_version\": \"4.26.1\",\n", " \"use_cache\": true,\n", " \"vocab_size\": 50257\n", "}\n", "\n", "Downloading (…)olve/main/vocab.json: 100% 1.04M/1.04M [00:01<00:00, 940kB/s]\n", "Downloading (…)olve/main/merges.txt: 100% 456k/456k [00:01<00:00, 413kB/s]\n", "Downloading (…)/main/tokenizer.json: 100% 1.36M/1.36M [00:01<00:00, 1.01MB/s]\n", "[INFO|tokenization_utils_base.py:1802] 2023-02-12 20:36:57,333 >> loading file vocab.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/vocab.json\n", "[INFO|tokenization_utils_base.py:1802] 2023-02-12 20:36:57,333 >> loading file merges.txt from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/merges.txt\n", "[INFO|tokenization_utils_base.py:1802] 2023-02-12 20:36:57,334 >> loading file tokenizer.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/tokenizer.json\n", "[INFO|tokenization_utils_base.py:1802] 2023-02-12 20:36:57,334 >> loading file added_tokens.json from cache at None\n", "[INFO|tokenization_utils_base.py:1802] 2023-02-12 20:36:57,334 >> loading file special_tokens_map.json from cache at None\n", "[INFO|tokenization_utils_base.py:1802] 2023-02-12 20:36:57,334 >> loading file tokenizer_config.json from cache at None\n", "[INFO|configuration_utils.py:660] 2023-02-12 20:36:57,334 >> loading configuration file config.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/config.json\n", "[INFO|configuration_utils.py:712] 2023-02-12 20:36:57,335 >> Model config GPT2Config {\n", " \"_name_or_path\": \"gpt2\",\n", " \"activation_function\": \"gelu_new\",\n", " \"architectures\": [\n", " \"GPT2LMHeadModel\"\n", " ],\n", " \"attn_pdrop\": 0.1,\n", " \"bos_token_id\": 50256,\n", " \"embd_pdrop\": 0.1,\n", " \"eos_token_id\": 50256,\n", " \"initializer_range\": 0.02,\n", " \"layer_norm_epsilon\": 1e-05,\n", " \"model_type\": \"gpt2\",\n", " \"n_ctx\": 1024,\n", " \"n_embd\": 768,\n", " \"n_head\": 12,\n", " \"n_inner\": null,\n", " \"n_layer\": 12,\n", " \"n_positions\": 1024,\n", " \"reorder_and_upcast_attn\": false,\n", " \"resid_pdrop\": 0.1,\n", " \"scale_attn_by_inverse_layer_idx\": false,\n", " \"scale_attn_weights\": true,\n", " \"summary_activation\": null,\n", " \"summary_first_dropout\": 0.1,\n", " \"summary_proj_to_labels\": true,\n", " \"summary_type\": \"cls_index\",\n", " \"summary_use_proj\": true,\n", " \"task_specific_params\": {\n", " \"text-generation\": {\n", " \"do_sample\": true,\n", " \"max_length\": 50\n", " }\n", " },\n", " \"transformers_version\": \"4.26.1\",\n", " \"use_cache\": true,\n", " \"vocab_size\": 50257\n", "}\n", "\n", "INFO:__main__:Using hidden states in model: True\n", "INFO:__main__:Using implementation from class: GPT2ForSequenceClassificationCustom\n", "Downloading (…)\"pytorch_model.bin\";: 100% 548M/548M [00:02<00:00, 261MB/s]\n", "[INFO|modeling_utils.py:2275] 2023-02-12 20:37:00,438 >> loading weights file pytorch_model.bin from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/pytorch_model.bin\n", "[INFO|modeling_utils.py:2857] 2023-02-12 20:37:03,142 >> All model checkpoint weights were used when initializing GPT2ForSequenceClassificationCustom.\n", "\n", "[WARNING|modeling_utils.py:2859] 2023-02-12 20:37:03,142 >> Some weights of GPT2ForSequenceClassificationCustom were not initialized from the model checkpoint at gpt2 and are newly initialized: ['score.dense_2.bias', 'score.out_proj.weight', 'score.dense_1_hidden.bias', 'score.dense_1_input.weight', 'score.dense_1_hidden.weight', 'score.dense_1_input.bias', 'score.dense_2.weight']\n", "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", "INFO:__main__:Freezing encoder weights\n", "INFO:__main__:Freezing layer 1\n", "INFO:__main__:Freezing layer 2\n", "INFO:__main__:Freezing layer 3\n", "INFO:__main__:Freezing layer 4\n", "INFO:__main__:Freezing layer 5\n", "INFO:__main__:Freezing layer 6\n", "INFO:__main__:Freezing layer 7\n", "INFO:__main__:Freezing layer 8\n", "INFO:__main__:Freezing layer 9\n", "INFO:__main__:Freezing layer 10\n", "INFO:__main__:Freezing layer 11\n", "INFO:__main__:Freezing layer 12\n", "INFO:__main__:Freezing layer 13\n", "INFO:__main__:Freezing layer 14\n", "INFO:__main__:Freezing layer 15\n", "INFO:__main__:Freezing layer 16\n", "INFO:__main__:Freezing layer 17\n", "INFO:__main__:Freezing layer 18\n", "INFO:__main__:Freezing layer 19\n", "INFO:__main__:Freezing layer 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"INFO:__main__:Ignoring layer 154\n", "INFO:__main__:Ignoring layer 155\n", "[ERROR|tokenization_utils_base.py:1042] 2023-02-12 20:37:03,155 >> Using pad_token, but it is not set yet.\n", "INFO:__main__:Set PAD token to EOS: <|endoftext|>\n", "Running tokenizer on dataset: 0% 0/16 [00:00> The following columns in the training set don't have a corresponding argument in `GPT2ForSequenceClassificationCustom.forward` and have been ignored: text. If text are not expected by `GPT2ForSequenceClassificationCustom.forward`, you can safely ignore this message.\n", "/usr/local/lib/python3.8/dist-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n", " warnings.warn(\n", "[INFO|trainer.py:1650] 2023-02-12 20:37:12,747 >> ***** Running training *****\n", "[INFO|trainer.py:1651] 2023-02-12 20:37:12,747 >> Num examples = 16000\n", "[INFO|trainer.py:1652] 2023-02-12 20:37:12,748 >> Num Epochs = 5\n", "[INFO|trainer.py:1653] 2023-02-12 20:37:12,748 >> Instantaneous batch size per device = 24\n", "[INFO|trainer.py:1654] 2023-02-12 20:37:12,748 >> Total train batch size (w. parallel, distributed & accumulation) = 24\n", "[INFO|trainer.py:1655] 2023-02-12 20:37:12,748 >> Gradient Accumulation steps = 1\n", "[INFO|trainer.py:1656] 2023-02-12 20:37:12,748 >> Total optimization steps = 3335\n", "[INFO|trainer.py:1657] 2023-02-12 20:37:12,749 >> Number of trainable parameters = 68517888\n", "{'loss': 1.0593, 'learning_rate': 1.7001499250374815e-05, 'epoch': 0.75}\n", " 15% 500/3335 [03:54<22:04, 2.14it/s][INFO|trainer.py:2709] 2023-02-12 20:41:07,509 >> Saving model checkpoint to out/imdb-5k/gpt2/checkpoint-500\n", "[INFO|configuration_utils.py:453] 2023-02-12 20:41:07,510 >> Configuration saved in out/imdb-5k/gpt2/checkpoint-500/config.json\n", "[INFO|modeling_utils.py:1704] 2023-02-12 20:41:09,283 >> Model weights saved in out/imdb-5k/gpt2/checkpoint-500/pytorch_model.bin\n", "[INFO|tokenization_utils_base.py:2160] 2023-02-12 20:41:09,284 >> tokenizer config file saved in out/imdb-5k/gpt2/checkpoint-500/tokenizer_config.json\n", "[INFO|tokenization_utils_base.py:2167] 2023-02-12 20:41:09,284 >> Special tokens file saved in out/imdb-5k/gpt2/checkpoint-500/special_tokens_map.json\n", "{'loss': 0.3829, 'learning_rate': 1.4002998500749626e-05, 'epoch': 1.5}\n", " 30% 1000/3335 [07:52<18:11, 2.14it/s][INFO|trainer.py:2709] 2023-02-12 20:45:05,515 >> Saving model checkpoint to out/imdb-5k/gpt2/checkpoint-1000\n", "[INFO|configuration_utils.py:453] 2023-02-12 20:45:05,516 >> Configuration saved in out/imdb-5k/gpt2/checkpoint-1000/config.json\n", "[INFO|modeling_utils.py:1704] 2023-02-12 20:45:07,205 >> Model weights saved in out/imdb-5k/gpt2/checkpoint-1000/pytorch_model.bin\n", "[INFO|tokenization_utils_base.py:2160] 2023-02-12 20:45:07,205 >> tokenizer config file saved in out/imdb-5k/gpt2/checkpoint-1000/tokenizer_config.json\n", "[INFO|tokenization_utils_base.py:2167] 2023-02-12 20:45:07,205 >> Special tokens file saved in out/imdb-5k/gpt2/checkpoint-1000/special_tokens_map.json\n", "{'loss': 0.256, 'learning_rate': 1.100449775112444e-05, 'epoch': 2.25}\n", " 45% 1500/3335 [11:50<14:19, 2.13it/s][INFO|trainer.py:2709] 2023-02-12 20:49:03,661 >> Saving model checkpoint to out/imdb-5k/gpt2/checkpoint-1500\n", "[INFO|configuration_utils.py:453] 2023-02-12 20:49:03,662 >> Configuration saved in out/imdb-5k/gpt2/checkpoint-1500/config.json\n", "[INFO|modeling_utils.py:1704] 2023-02-12 20:49:05,330 >> Model weights saved in out/imdb-5k/gpt2/checkpoint-1500/pytorch_model.bin\n", "[INFO|tokenization_utils_base.py:2160] 2023-02-12 20:49:05,331 >> tokenizer config file saved in out/imdb-5k/gpt2/checkpoint-1500/tokenizer_config.json\n", "[INFO|tokenization_utils_base.py:2167] 2023-02-12 20:49:05,331 >> Special tokens file saved in out/imdb-5k/gpt2/checkpoint-1500/special_tokens_map.json\n", "{'loss': 0.2101, 'learning_rate': 8.005997001499251e-06, 'epoch': 3.0}\n", " 60% 2000/3335 [15:49<10:24, 2.14it/s][INFO|trainer.py:2709] 2023-02-12 20:53:01,805 >> Saving model checkpoint to out/imdb-5k/gpt2/checkpoint-2000\n", "[INFO|configuration_utils.py:453] 2023-02-12 20:53:01,806 >> Configuration saved in out/imdb-5k/gpt2/checkpoint-2000/config.json\n", "[INFO|modeling_utils.py:1704] 2023-02-12 20:53:03,476 >> Model weights saved in out/imdb-5k/gpt2/checkpoint-2000/pytorch_model.bin\n", "[INFO|tokenization_utils_base.py:2160] 2023-02-12 20:53:03,476 >> tokenizer config file saved in out/imdb-5k/gpt2/checkpoint-2000/tokenizer_config.json\n", "[INFO|tokenization_utils_base.py:2167] 2023-02-12 20:53:03,476 >> Special tokens file saved in out/imdb-5k/gpt2/checkpoint-2000/special_tokens_map.json\n", "{'loss': 0.17, 'learning_rate': 5.0074962518740634e-06, 'epoch': 3.75}\n", " 75% 2500/3335 [19:47<06:30, 2.14it/s][INFO|trainer.py:2709] 2023-02-12 20:56:59,823 >> Saving model checkpoint to out/imdb-5k/gpt2/checkpoint-2500\n", "[INFO|configuration_utils.py:453] 2023-02-12 20:56:59,824 >> Configuration saved in out/imdb-5k/gpt2/checkpoint-2500/config.json\n", "[INFO|modeling_utils.py:1704] 2023-02-12 20:57:01,504 >> Model weights saved in out/imdb-5k/gpt2/checkpoint-2500/pytorch_model.bin\n", "[INFO|tokenization_utils_base.py:2160] 2023-02-12 20:57:01,505 >> tokenizer config file saved in out/imdb-5k/gpt2/checkpoint-2500/tokenizer_config.json\n", "[INFO|tokenization_utils_base.py:2167] 2023-02-12 20:57:01,505 >> Special tokens file saved in out/imdb-5k/gpt2/checkpoint-2500/special_tokens_map.json\n", "{'loss': 0.1569, 'learning_rate': 2.008995502248876e-06, 'epoch': 4.5}\n", " 90% 3000/3335 [23:44<02:36, 2.14it/s][INFO|trainer.py:2709] 2023-02-12 21:00:57,746 >> Saving model checkpoint to out/imdb-5k/gpt2/checkpoint-3000\n", "[INFO|configuration_utils.py:453] 2023-02-12 21:00:57,747 >> Configuration saved in out/imdb-5k/gpt2/checkpoint-3000/config.json\n", "[INFO|modeling_utils.py:1704] 2023-02-12 21:00:59,386 >> Model weights saved in out/imdb-5k/gpt2/checkpoint-3000/pytorch_model.bin\n", "[INFO|tokenization_utils_base.py:2160] 2023-02-12 21:00:59,387 >> tokenizer config file saved in out/imdb-5k/gpt2/checkpoint-3000/tokenizer_config.json\n", "[INFO|tokenization_utils_base.py:2167] 2023-02-12 21:00:59,387 >> Special tokens file saved in out/imdb-5k/gpt2/checkpoint-3000/special_tokens_map.json\n", "100% 3335/3335 [26:25<00:00, 2.36it/s][INFO|trainer.py:1901] 2023-02-12 21:03:38,497 >> \n", "\n", "Training completed. Do not forget to share your model on huggingface.co/models =)\n", "\n", "\n", "{'train_runtime': 1585.7622, 'train_samples_per_second': 50.449, 'train_steps_per_second': 2.103, 'train_loss': 0.35007504373118614, 'epoch': 5.0}\n", "100% 3335/3335 [26:25<00:00, 2.10it/s]\n", "[INFO|trainer.py:2709] 2023-02-12 21:03:38,514 >> Saving model checkpoint to out/imdb-5k/gpt2\n", "[INFO|configuration_utils.py:453] 2023-02-12 21:03:38,515 >> Configuration saved in out/imdb-5k/gpt2/config.json\n", "[INFO|modeling_utils.py:1704] 2023-02-12 21:03:40,135 >> Model weights saved in out/imdb-5k/gpt2/pytorch_model.bin\n", "[INFO|tokenization_utils_base.py:2160] 2023-02-12 21:03:40,136 >> tokenizer config file saved in out/imdb-5k/gpt2/tokenizer_config.json\n", "[INFO|tokenization_utils_base.py:2167] 2023-02-12 21:03:40,136 >> Special tokens file saved in out/imdb-5k/gpt2/special_tokens_map.json\n", "***** train metrics *****\n", " epoch = 5.0\n", " train_loss = 0.3501\n", " train_runtime = 0:26:25.76\n", " train_samples = 16000\n", " train_samples_per_second = 50.449\n", " train_steps_per_second = 2.103\n", "INFO:__main__:*** Evaluate ***\n", "[INFO|trainer.py:710] 2023-02-12 21:03:40,251 >> The following columns in the evaluation set don't have a corresponding argument in `GPT2ForSequenceClassificationCustom.forward` and have been ignored: text. If text are not expected by `GPT2ForSequenceClassificationCustom.forward`, you can safely ignore this message.\n", "[INFO|trainer.py:2964] 2023-02-12 21:03:40,336 >> ***** Running Evaluation *****\n", "[INFO|trainer.py:2966] 2023-02-12 21:03:40,336 >> Num examples = 637\n", "[INFO|trainer.py:2969] 2023-02-12 21:03:40,337 >> Batch size = 24\n", "100% 27/27 [00:04<00:00, 5.63it/s]\n", "***** eval metrics *****\n", " epoch = 5.0\n", " eval_accuracy = 0.9498\n", " eval_loss = 0.1357\n", " eval_runtime = 0:00:05.07\n", " eval_samples = 637\n", " eval_samples_per_second = 125.597\n", " eval_steps_per_second = 5.324\n", "INFO:__main__:*** Predict ***\n", "[INFO|trainer.py:710] 2023-02-12 21:03:45,413 >> The following columns in the test set don't have a corresponding argument in `GPT2ForSequenceClassificationCustom.forward` and have been ignored: text. If text are not expected by `GPT2ForSequenceClassificationCustom.forward`, you can safely ignore this message.\n", "[INFO|trainer.py:2964] 2023-02-12 21:03:45,415 >> ***** Running Prediction *****\n", "[INFO|trainer.py:2966] 2023-02-12 21:03:45,415 >> Num examples = 639\n", "[INFO|trainer.py:2969] 2023-02-12 21:03:45,415 >> Batch size = 24\n", "100% 27/27 [00:04<00:00, 5.62it/s]\n", "INFO:__main__:***** Predict results None *****\n", "[INFO|modelcard.py:449] 2023-02-12 21:03:51,543 >> Dropping the following result as it does not have all the necessary fields:\n", "{'task': {'name': 'Text Classification', 'type': 'text-classification'}, 'metrics': [{'name': 'Accuracy', 'type': 'accuracy', 'value': 0.9497645497322083}]}\n" ] } ] } ] }