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BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa

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BATCH_SIZE=8

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LEARNING_RATE=5e-05
MAX_LENGTH=512
FOLD=6

Files changed (6) hide show
  1. README.md +13 -13
  2. pytorch_model.bin +1 -1
  3. runs/Sep12_11-10-36_f75bc58113e9/events.out.tfevents.1631445926.f75bc58113e9.87.20 +3 -0
  4. runs/Sep12_11-25-29_f75bc58113e9/1631445934.2590873/events.out.tfevents.1631445934.f75bc58113e9.87.22 +3 -0
  5. runs/Sep12_11-25-29_f75bc58113e9/events.out.tfevents.1631445934.f75bc58113e9.87.21 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.4
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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
@@ -25,8 +25,8 @@ should probably proofread and complete it, then remove this comment. -->
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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 None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.7283
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- - Accuracy: 0.4
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  ## Model description
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@@ -57,16 +57,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 57 | 0.9481 | 0.56 |
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- | No log | 2.0 | 114 | 1.0163 | 0.56 |
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- | No log | 3.0 | 171 | 1.1452 | 0.38 |
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- | No log | 4.0 | 228 | 1.9038 | 0.54 |
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- | No log | 5.0 | 285 | 2.5529 | 0.4 |
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- | No log | 6.0 | 342 | 3.3545 | 0.42 |
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- | No log | 7.0 | 399 | 3.4529 | 0.44 |
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- | No log | 8.0 | 456 | 3.5855 | 0.4 |
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- | 0.3564 | 9.0 | 513 | 3.7481 | 0.38 |
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- | 0.3564 | 10.0 | 570 | 3.7283 | 0.4 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.58
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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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  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 None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.3170
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+ - Accuracy: 0.58
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 57 | 1.0118 | 0.32 |
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+ | No log | 2.0 | 114 | 0.9242 | 0.58 |
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+ | No log | 3.0 | 171 | 1.1096 | 0.42 |
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+ | No log | 4.0 | 228 | 1.0027 | 0.5 |
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+ | No log | 5.0 | 285 | 1.5517 | 0.5 |
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+ | No log | 6.0 | 342 | 1.7520 | 0.56 |
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+ | No log | 7.0 | 399 | 2.2123 | 0.56 |
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+ | No log | 8.0 | 456 | 2.1874 | 0.6 |
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+ | 0.4415 | 9.0 | 513 | 2.2495 | 0.58 |
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+ | 0.4415 | 10.0 | 570 | 2.3170 | 0.58 |
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  ### Framework versions
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