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Dagobert42
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distilbert-base-uncased-biored-augmented

Token Classification
Transformers
Safetensors
English
distilbert
low-resource NER
token_classification
biomedicine
medical NER
Generated from Trainer
Inference Endpoints
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Dagobert42 commited on
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1 Parent(s): 032a69b

Push ../models/distilbert-base-uncased/biored-augmentations-only/ trained on biored-train_200_splits.pt (200 samples)

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Files changed (3) hide show
  1. README.md +10 -11
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -28,12 +28,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the bigbio/biored dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5688
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- - Accuracy: 0.7988
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- - Precision: 0.6103
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- - Recall: 0.5421
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- - F1: 0.5557
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- - Weighted F1: 0.7942
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  ## Model description
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@@ -64,11 +64,10 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Weighted F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
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- | No log | 1.0 | 25 | 0.6074 | 0.7859 | 0.587 | 0.4553 | 0.5026 | 0.7631 |
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- | No log | 2.0 | 50 | 0.6028 | 0.7876 | 0.5625 | 0.535 | 0.5376 | 0.7785 |
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- | No log | 3.0 | 75 | 0.5867 | 0.7942 | 0.5756 | 0.5357 | 0.5464 | 0.786 |
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- | No log | 4.0 | 100 | 0.5924 | 0.7973 | 0.5914 | 0.5259 | 0.5454 | 0.7854 |
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- | No log | 5.0 | 125 | 0.5903 | 0.7989 | 0.5754 | 0.5289 | 0.5478 | 0.7876 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the bigbio/biored dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5692
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+ - Accuracy: 0.7978
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+ - Precision: 0.5993
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+ - Recall: 0.5337
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+ - F1: 0.5536
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+ - Weighted F1: 0.7929
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Weighted F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
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+ | No log | 1.0 | 25 | 0.6037 | 0.7824 | 0.5931 | 0.4937 | 0.5272 | 0.7719 |
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+ | No log | 2.0 | 50 | 0.5858 | 0.7932 | 0.6023 | 0.5298 | 0.5511 | 0.7849 |
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+ | No log | 3.0 | 75 | 0.5887 | 0.795 | 0.5757 | 0.5283 | 0.544 | 0.7842 |
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+ | No log | 4.0 | 100 | 0.5890 | 0.7937 | 0.5911 | 0.5331 | 0.5466 | 0.7864 |
 
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  ### Framework versions
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