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--- |
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library_name: transformers |
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license: other |
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base_model: DedalusHealthCare/tinybert-mlm-en |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: tinybert |
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results: [] |
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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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should probably proofread and complete it, then remove this comment. --> |
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# tinybert |
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This model is a fine-tuned version of [DedalusHealthCare/tinybert-mlm-en](https://huggingface.co/DedalusHealthCare/tinybert-mlm-en) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5776 |
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- Accuracy: 0.9816 |
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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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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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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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| 0.7155 | 0.2857 | 1 | 0.7256 | 0.1969 | 0.0437 | 0.0224 | 1.0 | |
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| 0.7155 | 0.5714 | 2 | 0.7204 | 0.2283 | 0.0455 | 0.0233 | 1.0 | |
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| 0.7155 | 0.8571 | 3 | 0.7102 | 0.3333 | 0.0451 | 0.0232 | 0.8571 | |
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| 0.7155 | 1.1429 | 4 | 0.6954 | 0.4803 | 0.0388 | 0.0201 | 0.5714 | |
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| 0.7155 | 1.4286 | 5 | 0.6763 | 0.7008 | 0.0500 | 0.0265 | 0.4286 | |
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| 0.7155 | 1.7143 | 6 | 0.6533 | 0.8530 | 0.0345 | 0.0196 | 0.1429 | |
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| 0.7155 | 2.0 | 7 | 0.6268 | 0.9580 | 0.0 | 0.0 | 0.0 | |
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| 0.7155 | 2.2857 | 8 | 0.6016 | 0.9816 | 0.0 | 0.0 | 0.0 | |
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| 0.7155 | 2.5714 | 9 | 0.5776 | 0.9816 | 0.0 | 0.0 | 0.0 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 2.16.0 |
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- Tokenizers 0.20.3 |
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