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sgugger
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finetuned-bert

Text Classification
Transformers
PyTorch
Safetensors
bert
generated_from_trainer
Inference Endpoints
Model card Files Community
3
sgugger commited on
Commit
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1 Parent(s): 1f747dd

add model

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Files changed (3) hide show
  1. README.md +7 -7
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -20,7 +20,7 @@ model_index:
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  metric:
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  name: F1
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  type: f1
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- value: 0.89419795221843
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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
@@ -30,9 +30,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the glue dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4555
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- - Accuracy: 0.8480
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- - F1: 0.8942
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  ## Model description
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@@ -63,9 +63,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.5479 | 1.0 | 230 | 0.3981 | 0.8235 | 0.8796 |
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- | 0.3194 | 2.0 | 460 | 0.3810 | 0.8431 | 0.8912 |
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- | 0.1372 | 3.0 | 690 | 0.4555 | 0.8480 | 0.8942 |
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  ### Framework versions
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  metric:
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  name: F1
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  type: f1
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+ value: 0.9125214408233276
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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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the glue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3916
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+ - Accuracy: 0.875
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+ - F1: 0.9125
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.581 | 1.0 | 230 | 0.4086 | 0.8260 | 0.8711 |
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+ | 0.366 | 2.0 | 460 | 0.3758 | 0.8480 | 0.8963 |
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+ | 0.2328 | 3.0 | 690 | 0.3916 | 0.875 | 0.9125 |
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  ### Framework versions
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