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--- |
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license: mit |
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base_model: prajjwal1/bert-tiny |
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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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model-index: |
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- name: BP-INT03 |
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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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# BP-INT03 |
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This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3220 |
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- Accuracy: 0.89 |
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- F1: 0.8889 |
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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: 16 |
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- eval_batch_size: 16 |
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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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| No log | 0.0 | 50 | 0.6958 | 0.43 | 0.2586 | |
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| No log | 0.01 | 100 | 0.6890 | 0.67 | 0.6043 | |
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| No log | 0.01 | 150 | 0.6814 | 0.57 | 0.4139 | |
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| No log | 0.02 | 200 | 0.6723 | 0.57 | 0.4139 | |
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| No log | 0.02 | 250 | 0.6289 | 0.81 | 0.8103 | |
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| No log | 0.03 | 300 | 0.5298 | 0.82 | 0.8207 | |
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| No log | 0.03 | 350 | 0.4480 | 0.88 | 0.8796 | |
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| No log | 0.04 | 400 | 0.4042 | 0.89 | 0.8889 | |
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| No log | 0.04 | 450 | 0.3688 | 0.9 | 0.8988 | |
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| 0.6099 | 0.05 | 500 | 0.3615 | 0.89 | 0.8889 | |
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| 0.6099 | 0.05 | 550 | 0.3542 | 0.89 | 0.8889 | |
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| 0.6099 | 0.06 | 600 | 0.3443 | 0.89 | 0.8889 | |
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| 0.6099 | 0.06 | 650 | 0.3300 | 0.89 | 0.8889 | |
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| 0.6099 | 0.07 | 700 | 0.3196 | 0.89 | 0.8889 | |
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| 0.6099 | 0.07 | 750 | 0.3220 | 0.89 | 0.8889 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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