From c708f9093fe7d1bb161d6949c8f461ca74f3da32 Mon Sep 17 00:00:00 2001 From: Jakub Adamski Date: Sun, 12 Feb 2023 14:22:43 +0100 Subject: [PATCH] T5 improvement --- projekt/README.md | 8 +- projekt/T5_sms_spam.ipynb | 1013 +++++++++++++++++++------------------ 2 files changed, 528 insertions(+), 493 deletions(-) diff --git a/projekt/README.md b/projekt/README.md index 92e3f4a..40b2554 100644 --- a/projekt/README.md +++ b/projekt/README.md @@ -47,15 +47,15 @@ Najważniejsze cechy: Najważniejsze cechy: - wytrenowany model t5-base - typ modelu transformers.T5ForConditionalGeneration -- input modelu - treść smsa -- output modelu - tekstowo klasa 1 'conversation' lub klasa 2 'advertising' +- input modelu - 'binary classification: ' + treść smsa +- output modelu - tekstowo '1' lub '0' - finetuning na zbiorze treningowym - adamW optimizer - learning rate 3e-4 - 16 batch size - 4 epoch -- Accuracy: 0% -- MCC: 0 +- Accuracy: 74% +- MCC: 0.190 ### Zero-shot Transformer Encoder-Decoder - FLAN-T5 Najważniejsze cechy: diff --git a/projekt/T5_sms_spam.ipynb b/projekt/T5_sms_spam.ipynb index ecafe51..cc354b3 100644 --- a/projekt/T5_sms_spam.ipynb +++ b/projekt/T5_sms_spam.ipynb @@ -16,7 +16,7 @@ "accelerator": "GPU", "widgets": { "application/vnd.jupyter.widget-state+json": { - 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"outputId": "87f24c1e-cb25-4b5a-b786-6f3bcbc0b96f" + "outputId": "b8dfca85-8b7a-4321-da77-ec7eea1843e9" }, "execution_count": 3, "outputs": [ @@ -3644,7 +3644,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "99a8b62c0eb9498a801d33b890ff7bed" + "model_id": "137fa30b14f34f57a0beb8a6c6e60cf5" } }, "metadata": {} @@ -3658,7 +3658,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "0b9435ced6e64d5b9a8817c10800df73" + "model_id": "47463520a286401ba3d5d29fce07ede5" } }, "metadata": {} @@ -3672,7 +3672,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "748c273b887042158812dc3ac1491537" + "model_id": "0926a24353a94b82a8e405ec72bef775" } }, "metadata": {} @@ -3693,7 +3693,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "c3f39c4d26334407bf94756b5111bafa" + "model_id": "320ba3e1e74541288c307eedbd5e2754" } }, "metadata": {} @@ -3707,7 +3707,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "52eb6c7623a34694a19e12a88cff244e" + "model_id": "a950c7427a174b22abdd17fb7710ece7" } }, "metadata": {} @@ -3728,7 +3728,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "dcd34a760b324e6a94e219a9e10e557b" + "model_id": "fddd4ee4bc054b0f90ed88018fc3e3a0" } }, "metadata": {} @@ -3745,7 +3745,7 @@ "base_uri": "https://localhost:8080/" }, "id": "JKFHPko3OnAV", - "outputId": "a94fa7c1-ab93-4473-d06a-61a8c50d8783" + "outputId": "2048bc4f-4d5f-45e4-e5c9-0be61d9d7349" }, "execution_count": 4, "outputs": [ @@ -3777,13 +3777,13 @@ "parsed_dataset = []\n", "\n", "for row in dataset['train']:\n", - " text = row['sms']\n", + " text = \"binary classification: \" + row['sms'].replace(\"\\n\", \"\")\n", " new_row = {}\n", " new_row['sms'] = text\n", " if row['label'] == 0:\n", - " new_row['label'] = \"conversation\"\n", + " new_row['label'] = \"0\"\n", " else:\n", - " new_row['label'] = \"advertising\"\n", + " new_row['label'] = \"1\"\n", " parsed_dataset.append(new_row)\n", "\n", "parsed_dataset[0]" @@ -3793,7 +3793,7 @@ "base_uri": "https://localhost:8080/" }, "id": "1boUF-YiY3_y", - "outputId": "15412aef-de85-43ce-ad3b-f88283a242a0" + "outputId": "fed6fa9c-8699-4727-ae1b-37475f831b61" }, "execution_count": 5, "outputs": [ @@ -3801,8 +3801,8 @@ "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': 'conversation'}" + "{'sms': 'binary classification: Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...',\n", + " 'label': '0'}" ] }, "metadata": {}, @@ -3838,34 +3838,34 @@ "metadata": { "colab": { "base_uri": "https://localhost:8080/", - "height": 185, + "height": 203, "referenced_widgets": [ - "54ce84849a974330a66e1100086a8fed", - "4efdba3661464381a034ba90eed898dc", - "d6e70f45ef8f426e8a9f1646e4bfdb2f", - "a6b434b5186341bbb2e3a6b5772f307f", - "eb2079320deb4ef5aa5624e164689b4e", - "88f741767e6845dda901e2f17fd978e1", - "d8bd3441499c405cbea7b6b61f7636ad", - "af6d44105eb8435cbc34fa902e4303b9", - "e5dc73086a7d48a5a75274ecf7e1e83e", - "7bad80b954c74f8995f9c572a2831b6f", - "6358c42c34a74dfc8df0101076eb2274", - "3806842991b04a19a315223c4f0d05b0", - "0f9e34991e634982a37ed4474939a614", - "6fd3d1538419439db78ae1940e6ecd95", - "968e624fbe4b49d8b22ba35237f29f04", - "490d54e698024024a0376e0c5aa57afa", - "9c921a01f9f44ef6b6b0867fbce29d4e", - "d932c14e5642431da3490fda711b855a", - "e66eea96fb8d467085ff05b14cef41f5", - "8ff90b6f1b204ceaa41c09c48bdb4a95", - "1c3c1fd4ebbf4363aa9c7b7df4fb96a7", - "7febee22767b48ed8ffb31b2e86e2bde" + "6e2b903343ad49c89339a38a1c626619", + "b1e96f5c00d048c69c1c0fadeb31dcd9", + "ec994f6daafb4ef8a08371f2394918dd", + "699d9f4479854372ada35ab38fe80352", + "cb36ca390eac4c76ad8cfbcbdb5b6950", + "5ffe2a0b8e3342a9b764fbbdf1395f1c", + "ea92e7a968d4479e842c368ece4b60c1", + "95a4496f03414cf8a8d7cf5e6cc3f37b", + "7b1d15df592048fe8a8c043e7a8461ad", + "cc73442788a3462a8d5d53c9c799df7a", + "ee75218b2c4047fdb265df7a54feea78", + "e720c7e5ef0849918eb6e7123673c95e", + "8b2ff14cab9941388b547140d06e1dd5", + "0eb67bf20ecf4cc0b5f3bd0589440e6b", + "4e976d7959e640f4b098d9a02320f228", + "48de3465dc194fff9903fd3813aae91a", + "29558f7cc7574024879d274548ac4cd7", + "ce5531904574465d84d65365b0fc2951", + "10cc03c556cf4fb791697277b3deef35", + "2113acabfb014e7ab55d099d28845914", + "504b320daae543b78b8777cebbe65dea", + "5ea6f5fa80184fe58ef86a536ec0f8f0" ] }, "id": "q5Jz0E_oPMBr", - "outputId": "57650e4c-558f-46aa-e08f-0362ab53e2e8" + "outputId": "bbe8a564-fee5-42ef-da4d-04ae4af111db" }, "execution_count": 7, "outputs": [ @@ -3878,7 +3878,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "54ce84849a974330a66e1100086a8fed" + "model_id": "6e2b903343ad49c89339a38a1c626619" } }, "metadata": {} @@ -3892,7 +3892,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "3806842991b04a19a315223c4f0d05b0" + "model_id": "e720c7e5ef0849918eb6e7123673c95e" } }, "metadata": {} @@ -3924,7 +3924,7 @@ "base_uri": "https://localhost:8080/" }, "id": "dfxJQpoePsvI", - "outputId": "713d0aed-1350-44f9-e59d-e4a2f8b7a0b3" + "outputId": "fa44a9cd-aff1-4b64-957e-52595dad7472" }, "execution_count": 8, "outputs": [ @@ -3932,10 +3932,9 @@ "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", - "\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" + "Original: binary classification: Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...\n", + "Tokenized: ['▁binary', '▁classification', ':', '▁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: [14865, 13774, 10, 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" ] } ] @@ -3965,7 +3964,7 @@ "base_uri": "https://localhost:8080/" }, "id": "7uNUkixPU85O", - "outputId": "6a83d1cb-629d-4725-e3a2-5c60f9962108" + "outputId": "2ec78c60-f5ae-4201-c8e5-30208c94efab" }, "execution_count": 9, "outputs": [ @@ -3973,7 +3972,7 @@ "output_type": "stream", "name": "stdout", "text": [ - "Max sentence length: 338\n" + "Max sentence length: 341\n" ] } ] @@ -3994,7 +3993,7 @@ "base_uri": "https://localhost:8080/" }, "id": "lj0issBznZfK", - "outputId": "38498917-ba97-472f-9012-5da83babab62" + "outputId": "2fb86f95-c0a0-45ea-a36d-a6b174f32aac" }, "execution_count": 10, "outputs": [ @@ -4002,7 +4001,7 @@ "output_type": "stream", "name": "stdout", "text": [ - "Max sentence length: 2\n" + "Max sentence length: 3\n" ] } ] @@ -4038,7 +4037,7 @@ " encoded_dict = tokenizer.encode_plus(\n", " sentence['sms'],\n", " add_special_tokens = True,\n", - " max_length = 340,\n", + " max_length = 341,\n", " padding = 'max_length',\n", " truncation=True,\n", " return_attention_mask = True,\n", @@ -4048,7 +4047,7 @@ " encoded_target_dict = tokenizer.encode_plus(\n", " sentence['label'],\n", " add_special_tokens = True,\n", - " max_length = 2,\n", + " max_length = 3,\n", " padding = 'max_length',\n", " truncation=True,\n", " return_attention_mask = True,\n", @@ -4072,7 +4071,7 @@ "base_uri": "https://localhost:8080/" }, "id": "Z28QYfLnSGxR", - "outputId": "9b98f987-7176-48cc-d298-f09f69c6eab7" + "outputId": "e90e2369-25d1-4fc1-b7fd-b805eaf1f5de" }, "execution_count": 12, "outputs": [ @@ -4080,11 +4079,11 @@ "output_type": "stream", "name": "stdout", "text": [ - "Original: {'sms': 'Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...\\n', 'label': 'conversation'}\n", - "Token IDs: tensor([ 1263, 552, 10081, 2444, 500, 6, 6139, 5, 5, 8144,\n", - " 163, 16, 8143, 159, 3, 29, 248, 296, 50, 3,\n", - " 15, 15385, 233, 17270, 132, 530, 3, 9, 3706, 8036,\n", - " 17, 233, 1, 0, 0, 0, 0, 0, 0, 0,\n", + "Original: {'sms': 'binary classification: Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...', 'label': '0'}\n", + "Token IDs: tensor([14865, 13774, 10, 1263, 552, 10081, 2444, 500, 6, 6139,\n", + " 5, 5, 8144, 163, 16, 8143, 159, 3, 29, 248,\n", + " 296, 50, 3, 15, 15385, 233, 17270, 132, 530, 3,\n", + " 9, 3706, 8036, 17, 233, 1, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", @@ -4114,8 +4113,9 @@ " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", - " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])\n", - "Label token IDs: tensor([3634, 1])\n" + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0])\n", + "Label token IDs: tensor([ 3, 632, 1])\n" ] } ] @@ -4161,7 +4161,7 @@ "base_uri": "https://localhost:8080/" }, "id": "Mm6vc6lLVW3l", - "outputId": "cfb15fb6-1daa-4b3c-df1b-5d0c862e8821" + "outputId": "af8a7007-791f-426c-c277-1c77a1fd9d78" }, "execution_count": 14, "outputs": [ @@ -4246,7 +4246,7 @@ "base_uri": "https://localhost:8080/" }, "id": "ANBCfNGnVwVk", - "outputId": "8db82471-22b2-450d-cb9d-ba86ce765fa2" + "outputId": "02086b95-30b8-4be0-aa4b-ac0041b4b007" }, "execution_count": 17, "outputs": [ @@ -4292,32 +4292,32 @@ "base_uri": "https://localhost:8080/", "height": 1000, "referenced_widgets": [ - "c4238a30a23f4a4995a64596a076f639", - "7008395271204caba9d2a70e886f3fb7", - "91fe75c3703e49e2b9200eb32465979a", - "605fe093ee154e1eafda5f92c07712ef", - "63343a6f0a2a4f66b878afc18d408c1c", - "fc24763fbd70457fbb2a67883ec38a67", - "7ba8e63a4e1645ebad9829af1706fb1d", - "1aeec94f6aed4d6fa9ef94b5e8011f95", - "7ab80f2dc4bd4bc4b4d28bff719068e2", - "ab5aa9e15b894bf6aec2ed8d7949d4fb", - "5aff4f72159e4187adf00959d8863017", - "52e83e2e748f4c79b789d0354f4e941b", - "ef0f5971cb444d8f8c5c1ace4d8ebe81", - "64885f8157264a1297bab372bf8a7fb5", - "6b3444ddd6d24f448631e3e86d992241", - "7e0aaf3e4b5b4bbc9c8120d9e5c00d8d", - "51c2d890c6874141a0d5ecc0eb89a282", - "1ec01f40f98f47e3aae79a9f871d9df1", - "f208555568824dd9a800555cc17182be", - "5fd3c6d56ef644ebaff4da4bffa470a5", - "5167e08d346f47468249d2f40b262792", - "904d0e8e3a2b443f9e90652d78ecff95" + "b1d7a5cf900b48408e515baa4c66a1cd", + "6846a2acd95b45a3a0e2cb79f552f0c0", + "fce901d34cc34feeb92854999e98c0f9", + "5a89ce40643247fda326742531912a01", + "bcc7a0cd035e485680b41e7c4a78b8f8", + "bd0a578fefb44fb4b2662d59fd2ff12e", + "6585bd6115c047fd881c0bfd323142f0", + "dbc7f7aa90174ff68b5cc829a6fd8690", + "ca3a8e4611c6422380351b947882876a", + "2470365762844b62a09dc6fa818c4a09", + "3f2489ce0ae941a1a720c60a3052ee70", + "0795a8385c68409fb5539b9ea6756a47", + "05dfc6dc9f78483da34b2c6513315e7d", + "5cfe28a638cb42fc914dc81eb02a46f4", + "d061dcb2f3e840ec9ba6a6ec4d972619", + "df418dee3efd4da8aa57ca0044190b2e", + "9d3d394c756d4eabb0f3fd66ba8ef05a", + "00612595fa42467a83aa6e4b55343339", + "33521be9887b4c368915b4f8f2438440", + "990a862f07894fa9b9f08d3bb7e082ca", + "1b793ae9c46740bdbbec5e617a899683", + "cbfde7f5f0204417abdced523c5621e9" ] }, "id": "JKv9O8kfV2zZ", - "outputId": "0d41faa2-6857-4a67-d581-41383ffc0378" + "outputId": "b4b823d6-f7dc-4b78-a12b-4a2bae4e463f" }, "execution_count": 19, "outputs": [ @@ -4330,7 +4330,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "c4238a30a23f4a4995a64596a076f639" + "model_id": "b1d7a5cf900b48408e515baa4c66a1cd" } }, "metadata": {} @@ -4344,7 +4344,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "52e83e2e748f4c79b789d0354f4e941b" + "model_id": "0795a8385c68409fb5539b9ea6756a47" } }, "metadata": {} @@ -5216,6 +5216,7 @@ "\n", " t0 = time.time()\n", " total_train_loss = 0\n", + " total_train_acc = 0\n", "\n", " model.train()\n", "\n", @@ -5241,6 +5242,20 @@ " labels=lm_labels\n", " )\n", "\n", + " generated_ids = model.generate(\n", + " input_ids = b_input_ids,\n", + " attention_mask = b_input_mask, \n", + " max_length=2, \n", + " num_beams=2,\n", + " repetition_penalty=2.5, \n", + " length_penalty=1.0, \n", + " early_stopping=True\n", + " )\n", + "\n", + " preds = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=True) for g in generated_ids]\n", + " target = [tokenizer.decode(t, skip_special_tokens=True, clean_up_tokenization_spaces=True) for t in y]\n", + " total_train_acc += calculate_accuracy(preds, target) \n", + "\n", " loss = outputs['loss']\n", " total_train_loss += loss.item()\n", "\n", @@ -5250,11 +5265,13 @@ " optimizer.step()\n", " scheduler.step()\n", "\n", - " avg_train_loss = total_train_loss / len(train_dataloader) \n", + " avg_train_loss = total_train_loss / len(train_dataloader) \n", + " avg_train_acc = total_train_acc / len(train_dataloader) \n", " training_time = format_time(time.time() - t0)\n", "\n", " print(\"\")\n", " print(\" Average training loss: {0:.2f}\".format(avg_train_loss))\n", + " print(\" Average training acc: {0:.2f}\".format(avg_train_acc))\n", " print(\" Training epcoh took: {:}\".format(training_time))\n", " \n", " # ========================================\n", @@ -5318,6 +5335,7 @@ " {\n", " 'epoch': epoch_i + 1,\n", " 'Training Loss': avg_train_loss,\n", + " 'Training Accur.': avg_train_acc,\n", " 'Valid. Loss': avg_val_loss,\n", " 'Valid. Accur.': avg_val_accuracy,\n", " 'Training Time': training_time,\n", @@ -5335,7 +5353,7 @@ "base_uri": "https://localhost:8080/" }, "id": "xsHxfslka1u5", - "outputId": "c1d90548-6d70-4172-e0e2-e916eea141a6" + "outputId": "60bea81f-a963-4599-ca22-b1992c14a3e5" }, "execution_count": 25, "outputs": [ @@ -5346,74 +5364,78 @@ "\n", "======== Epoch 1 / 4 ========\n", "Training...\n", - " Batch 40 of 258. Elapsed: 0:00:46.\n", - " Batch 80 of 258. Elapsed: 0:01:32.\n", - " Batch 120 of 258. Elapsed: 0:02:17.\n", - " Batch 160 of 258. Elapsed: 0:03:02.\n", - " Batch 200 of 258. Elapsed: 0:03:47.\n", - " Batch 240 of 258. Elapsed: 0:04:33.\n", + " Batch 40 of 258. Elapsed: 0:01:06.\n", + " Batch 80 of 258. Elapsed: 0:02:13.\n", + " Batch 120 of 258. Elapsed: 0:03:22.\n", + " Batch 160 of 258. Elapsed: 0:04:32.\n", + " Batch 200 of 258. Elapsed: 0:05:42.\n", + " Batch 240 of 258. Elapsed: 0:06:52.\n", "\n", - " Average training loss: 0.02\n", - " Training epcoh took: 0:04:52\n", + " Average training loss: 0.09\n", + " Average training acc: 0.42\n", + " Training epcoh took: 0:07:22\n", "\n", "Running Validation...\n", - " Accuracy: 0.00\n", - " Validation took: 0:00:24\n", + " Accuracy: 0.68\n", + " Validation took: 0:00:25\n", " Validation Loss: 0.00\n", "\n", "======== Epoch 2 / 4 ========\n", "Training...\n", - " Batch 40 of 258. Elapsed: 0:00:45.\n", - " Batch 80 of 258. Elapsed: 0:01:31.\n", - " Batch 120 of 258. Elapsed: 0:02:16.\n", - " Batch 160 of 258. Elapsed: 0:03:01.\n", - " Batch 200 of 258. Elapsed: 0:03:46.\n", - " Batch 240 of 258. Elapsed: 0:04:32.\n", + " Batch 40 of 258. Elapsed: 0:01:10.\n", + " Batch 80 of 258. Elapsed: 0:02:19.\n", + " Batch 120 of 258. Elapsed: 0:03:29.\n", + " Batch 160 of 258. Elapsed: 0:04:39.\n", + " Batch 200 of 258. Elapsed: 0:05:48.\n", + " Batch 240 of 258. Elapsed: 0:06:58.\n", "\n", " Average training loss: 0.00\n", - " Training epcoh took: 0:04:52\n", + " Average training acc: 0.49\n", + " Training epcoh took: 0:07:28\n", "\n", "Running Validation...\n", - " Accuracy: 0.00\n", - " Validation took: 0:00:24\n", + " Accuracy: 0.72\n", + " Validation took: 0:00:25\n", " Validation Loss: 0.00\n", "\n", "======== Epoch 3 / 4 ========\n", "Training...\n", - " Batch 40 of 258. Elapsed: 0:00:45.\n", - " Batch 80 of 258. Elapsed: 0:01:30.\n", - " Batch 120 of 258. Elapsed: 0:02:15.\n", - " Batch 160 of 258. Elapsed: 0:03:01.\n", - " Batch 200 of 258. Elapsed: 0:03:46.\n", - " Batch 240 of 258. Elapsed: 0:04:31.\n", + " Batch 40 of 258. Elapsed: 0:01:10.\n", + " Batch 80 of 258. Elapsed: 0:02:19.\n", + " Batch 120 of 258. Elapsed: 0:03:29.\n", + " Batch 160 of 258. Elapsed: 0:04:39.\n", + " Batch 200 of 258. Elapsed: 0:05:49.\n", + " Batch 240 of 258. Elapsed: 0:06:58.\n", "\n", " Average training loss: 0.00\n", - " Training epcoh took: 0:04:51\n", + " Average training acc: 0.50\n", + " Training epcoh took: 0:07:29\n", "\n", "Running Validation...\n", - " Accuracy: 0.00\n", - " Validation took: 0:00:24\n", + " Accuracy: 0.72\n", + " Validation took: 0:00:25\n", " Validation Loss: 0.00\n", "\n", "======== Epoch 4 / 4 ========\n", "Training...\n", - " Batch 40 of 258. Elapsed: 0:00:45.\n", - " Batch 80 of 258. Elapsed: 0:01:30.\n", - " Batch 120 of 258. Elapsed: 0:02:16.\n", - " Batch 160 of 258. Elapsed: 0:03:01.\n", - " Batch 200 of 258. Elapsed: 0:03:46.\n", - " Batch 240 of 258. Elapsed: 0:04:31.\n", + " Batch 40 of 258. Elapsed: 0:01:10.\n", + " Batch 80 of 258. Elapsed: 0:02:19.\n", + " Batch 120 of 258. Elapsed: 0:03:29.\n", + " Batch 160 of 258. Elapsed: 0:04:39.\n", + " Batch 200 of 258. Elapsed: 0:05:49.\n", + " Batch 240 of 258. Elapsed: 0:06:58.\n", "\n", " Average training loss: 0.00\n", - " Training epcoh took: 0:04:51\n", + " Average training acc: 0.50\n", + " Training epcoh took: 0:07:29\n", "\n", "Running Validation...\n", - " Accuracy: 0.00\n", - " Validation took: 0:00:24\n", + " Accuracy: 0.72\n", + " Validation took: 0:00:25\n", " Validation Loss: 0.00\n", "\n", "Training complete!\n", - "Total training took 0:21:01 (h:mm:ss)\n" + "Total training took 0:31:29 (h:mm:ss)\n" ] } ] @@ -5441,10 +5463,10 @@ "metadata": { "colab": { "base_uri": "https://localhost:8080/", - "height": 206 + "height": 204 }, "id": "GjYqBrrO93Oh", - "outputId": "4a9cd46d-4c7c-447e-f98d-21f3cdd66c34" + "outputId": "d5742682-1cb4-4910-ab30-9424671b31e4" }, "execution_count": 26, "outputs": [ @@ -5452,16 +5474,23 @@ "output_type": "execute_result", "data": { "text/plain": [ - " Training Loss Valid. Loss Valid. Accur. Training Time Validation Time\n", - "epoch \n", - "1 1.84e-02 0.0 0.0 0:04:52 0:00:24\n", - "2 1.49e-06 0.0 0.0 0:04:52 0:00:24\n", - "3 4.64e-07 0.0 0.0 0:04:51 0:00:24\n", - "4 1.43e-07 0.0 0.0 0:04:51 0:00:24" + " Training Loss Training Accur. Valid. Loss Valid. Accur. \\\n", + "epoch \n", + "1 8.67e-02 0.42 1.46e-08 0.68 \n", + "2 2.02e-06 0.49 2.65e-10 0.72 \n", + "3 1.50e-06 0.50 0.00e+00 0.72 \n", + "4 1.10e-06 0.50 0.00e+00 0.72 \n", + "\n", + " Training Time Validation Time \n", + "epoch \n", + "1 0:07:22 0:00:25 \n", + "2 0:07:28 0:00:25 \n", + "3 0:07:29 0:00:25 \n", + "4 0:07:29 0:00:25 " ], "text/html": [ "\n", - "
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