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santis2
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bert-base-uncased-glue-mrpc

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results
Inference Endpoints
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End of training

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  1. README.md +7 -17
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -23,10 +23,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8382352941176471
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  - name: F1
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  type: f1
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- value: 0.8885135135135136
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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
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1675
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- - Accuracy: 0.8382
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- - F1: 0.8885
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  ## Model description
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@@ -63,23 +63,13 @@ The following hyperparameters were used during training:
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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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.3059 | 0.87 | 100 | 0.4943 | 0.8211 | 0.8809 |
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- | 0.2577 | 1.74 | 200 | 0.4251 | 0.8554 | 0.8981 |
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- | 0.1418 | 2.61 | 300 | 0.4819 | 0.8529 | 0.8936 |
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- | 0.0821 | 3.48 | 400 | 0.7154 | 0.8505 | 0.8913 |
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- | 0.0511 | 4.35 | 500 | 0.9418 | 0.8505 | 0.8950 |
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- | 0.0362 | 5.22 | 600 | 0.9225 | 0.8333 | 0.8803 |
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- | 0.0287 | 6.09 | 700 | 0.9822 | 0.8309 | 0.8816 |
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- | 0.0088 | 6.96 | 800 | 1.0204 | 0.8358 | 0.8851 |
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- | 0.0041 | 7.83 | 900 | 1.0580 | 0.8407 | 0.8873 |
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- | 0.0013 | 8.7 | 1000 | 1.1243 | 0.8407 | 0.8896 |
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- | 0.0027 | 9.57 | 1100 | 1.1675 | 0.8382 | 0.8885 |
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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: 0.8333333333333334
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  - name: F1
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  type: f1
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+ value: 0.8870431893687708
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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-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3979
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+ - Accuracy: 0.8333
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+ - F1: 0.8870
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  ## Model description
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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: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.5454 | 0.87 | 100 | 0.3979 | 0.8333 | 0.8870 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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