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google_mobilebert-uncased_fold_3

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google_mobilebert-uncased fold 3

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README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: nan
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- - Accuracy: 0.5413
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- - F1: 0.0
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- - Precision: 0.0
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- - Recall: 0.0
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  ## Model description
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@@ -51,15 +51,14 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 3
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- - mixed_precision_training: Native AMP
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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- |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---:|:---------:|:------:|
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- | 0.0 | 1.0 | 15481 | nan | 0.5413 | 0.0 | 0.0 | 0.0 |
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- | 0.0 | 2.0 | 30962 | nan | 0.5413 | 0.0 | 0.0 | 0.0 |
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- | 0.0 | 3.0 | 46443 | nan | 0.5413 | 0.0 | 0.0 | 0.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1173
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+ - Accuracy: 0.9583
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+ - F1: 0.9542
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+ - Precision: 0.9601
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+ - Recall: 0.9485
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  ## Model description
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 3
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.1216 | 1.0 | 15481 | 0.1380 | 0.9483 | 0.9423 | 0.9645 | 0.9211 |
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+ | 0.1359 | 2.0 | 30962 | 0.1113 | 0.9568 | 0.9528 | 0.9546 | 0.9510 |
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+ | 0.0927 | 3.0 | 46443 | 0.1173 | 0.9583 | 0.9542 | 0.9601 | 0.9485 |
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  ### Framework versions