| --- |
| library_name: transformers |
| license: other |
| base_model: DedalusHealthCare/tinybert-mlm-en |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: tinybert |
| 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. --> |
|
|
| # tinybert |
|
|
| This model is a fine-tuned version of [DedalusHealthCare/tinybert-mlm-en](https://huggingface.co/DedalusHealthCare/tinybert-mlm-en) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5185 |
| - Accuracy: 0.9816 |
| - F1: 0.0 |
| - Precision: 0.0 |
| - Recall: 0.0 |
|
|
| ## 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: 32 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:---:|:---------:|:------:| |
| | No log | 0.2857 | 1 | 0.6663 | 0.7953 | 0.0 | 0.0 | 0.0 | |
| | No log | 0.5714 | 2 | 0.6612 | 0.8189 | 0.0 | 0.0 | 0.0 | |
| | No log | 0.8571 | 3 | 0.6516 | 0.8766 | 0.0 | 0.0 | 0.0 | |
| | No log | 1.1429 | 4 | 0.6373 | 0.9081 | 0.0 | 0.0 | 0.0 | |
| | No log | 1.4286 | 5 | 0.6185 | 0.9423 | 0.0 | 0.0 | 0.0 | |
| | No log | 1.7143 | 6 | 0.5955 | 0.9685 | 0.0 | 0.0 | 0.0 | |
| | No log | 2.0 | 7 | 0.5687 | 0.9790 | 0.0 | 0.0 | 0.0 | |
| | No log | 2.2857 | 8 | 0.5431 | 0.9816 | 0.0 | 0.0 | 0.0 | |
| | No log | 2.5714 | 9 | 0.5185 | 0.9816 | 0.0 | 0.0 | 0.0 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.45.1 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 2.16.0 |
| - Tokenizers 0.20.3 |
|
|
