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bert-covid

Question Answering
Transformers
PyTorch
bert
Generated from Trainer
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bert-squad

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Files changed (8) hide show
  1. README.md +126 -0
  2. config.json +25 -0
  3. pytorch_model.bin +3 -0
  4. special_tokens_map.json +7 -0
  5. tokenizer.json +0 -0
  6. tokenizer_config.json +57 -0
  7. training_args.bin +3 -0
  8. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - covid_qa_deepset
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+ model-index:
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+ - name: bert-covid
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # bert-covid
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+
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+ This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the covid_qa_deepset dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6900
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 5.474 | 0.04 | 5 | 4.3730 |
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+ | 3.9933 | 0.09 | 10 | 3.2783 |
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+ | 3.0206 | 0.13 | 15 | 2.0289 |
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+ | 1.9741 | 0.18 | 20 | 1.3879 |
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+ | 1.4351 | 0.22 | 25 | 1.1733 |
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+ | 1.5916 | 0.26 | 30 | 1.1623 |
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+ | 0.5383 | 0.31 | 35 | 1.1952 |
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+ | 0.7776 | 0.35 | 40 | 1.1920 |
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+ | 1.1785 | 0.39 | 45 | 1.1216 |
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+ | 1.1334 | 0.44 | 50 | 1.0412 |
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+ | 0.7445 | 0.48 | 55 | 1.0829 |
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+ | 0.6512 | 0.53 | 60 | 1.0443 |
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+ | 0.7516 | 0.57 | 65 | 1.0089 |
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+ | 0.5953 | 0.61 | 70 | 0.9273 |
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+ | 0.8589 | 0.66 | 75 | 0.8947 |
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+ | 0.7561 | 0.7 | 80 | 0.9009 |
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+ | 0.9561 | 0.75 | 85 | 0.9006 |
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+ | 0.7731 | 0.79 | 90 | 0.8482 |
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+ | 0.8269 | 0.83 | 95 | 0.8380 |
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+ | 0.9884 | 0.88 | 100 | 0.8200 |
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+ | 0.9187 | 0.92 | 105 | 0.8775 |
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+ | 0.585 | 0.96 | 110 | 0.8499 |
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+ | 0.6835 | 1.01 | 115 | 0.8314 |
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+ | 0.6668 | 1.05 | 120 | 0.7491 |
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+ | 0.5558 | 1.1 | 125 | 0.7154 |
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+ | 0.4491 | 1.14 | 130 | 0.8212 |
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+ | 1.0667 | 1.18 | 135 | 0.8477 |
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+ | 0.4472 | 1.23 | 140 | 0.7636 |
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+ | 0.6892 | 1.27 | 145 | 0.7493 |
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+ | 0.66 | 1.32 | 150 | 0.6932 |
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+ | 0.5044 | 1.36 | 155 | 0.7675 |
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+ | 0.5329 | 1.4 | 160 | 0.7406 |
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+ | 0.2223 | 1.45 | 165 | 0.8099 |
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+ | 0.5495 | 1.49 | 170 | 0.8758 |
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+ | 0.5534 | 1.54 | 175 | 0.8476 |
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+ | 0.4962 | 1.58 | 180 | 0.7953 |
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+ | 0.7477 | 1.62 | 185 | 0.7610 |
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+ | 0.7293 | 1.67 | 190 | 0.8357 |
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+ | 0.6205 | 1.71 | 195 | 0.7339 |
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+ | 0.5687 | 1.75 | 200 | 0.6908 |
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+ | 0.884 | 1.8 | 205 | 0.6706 |
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+ | 0.5928 | 1.84 | 210 | 0.6546 |
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+ | 0.3209 | 1.89 | 215 | 0.6505 |
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+ | 0.7585 | 1.93 | 220 | 0.6486 |
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+ | 0.8501 | 1.97 | 225 | 0.6272 |
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+ | 0.1664 | 2.02 | 230 | 0.6211 |
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+ | 0.4483 | 2.06 | 235 | 0.6550 |
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+ | 0.3361 | 2.11 | 240 | 0.6604 |
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+ | 0.3085 | 2.15 | 245 | 0.6520 |
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+ | 0.2407 | 2.19 | 250 | 0.6695 |
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+ | 0.3418 | 2.24 | 255 | 0.6687 |
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+ | 0.3165 | 2.28 | 260 | 0.6730 |
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+ | 0.5811 | 2.32 | 265 | 0.6546 |
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+ | 0.3516 | 2.37 | 270 | 0.6579 |
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+ | 0.3136 | 2.41 | 275 | 0.6688 |
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+ | 0.2508 | 2.46 | 280 | 0.6921 |
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+ | 0.3463 | 2.5 | 285 | 0.7124 |
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+ | 0.3603 | 2.54 | 290 | 0.7160 |
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+ | 0.4455 | 2.59 | 295 | 0.6995 |
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+ | 0.5433 | 2.63 | 300 | 0.6919 |
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+ | 0.3411 | 2.68 | 305 | 0.6898 |
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+ | 0.6065 | 2.72 | 310 | 0.6922 |
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+ | 0.6258 | 2.76 | 315 | 0.6955 |
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+ | 0.283 | 2.81 | 320 | 0.7008 |
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+ | 0.6233 | 2.85 | 325 | 0.6988 |
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+ | 0.3899 | 2.89 | 330 | 0.6949 |
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+ | 0.238 | 2.94 | 335 | 0.6916 |
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+ | 0.3166 | 2.98 | 340 | 0.6900 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext",
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+ "architectures": [
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+ "BertForQuestionAnswering"
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.34.1",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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vocab.txt ADDED
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