| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: M12-BirtSimilarity-Mix-With-GlossBERT |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # M12-BirtSimilarity-Mix-With-GlossBERT |
|
|
| This model is a fine-tuned version of [aomar85/M12-BERT-SIMILIARITY](https://huggingface.co/aomar85/M12-BERT-SIMILIARITY) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2815 |
| - Accuracy: 0.9172 |
| - Precision: 0.8973 |
| - Recall: 0.9348 |
| - F1: 0.9157 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.2469 | 1.0 | 59883 | 0.2437 | 0.9159 | 0.8847 | 0.9488 | 0.9156 | |
| | 0.2302 | 2.0 | 119766 | 0.2884 | 0.9172 | 0.8862 | 0.9496 | 0.9168 | |
| | 0.2201 | 3.0 | 179649 | 0.2552 | 0.9177 | 0.8953 | 0.9385 | 0.9164 | |
| | 0.2045 | 4.0 | 239532 | 0.2815 | 0.9172 | 0.8973 | 0.9348 | 0.9157 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.21.3 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
