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--- |
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license: mit |
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base_model: microsoft/deberta-v3-small |
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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: kaggle-math |
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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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# kaggle-math |
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6024 |
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- Accuracy: 0.8204 |
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- F1: 0.8204 |
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- Precision: 0.8204 |
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- Recall: 0.8204 |
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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: 5e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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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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- lr_scheduler_warmup_steps: 500 |
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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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| 0.6125 | 1.0 | 680 | 0.8193 | 0.7782 | 0.7782 | 0.7782 | 0.7782 | |
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| 0.5557 | 2.0 | 1360 | 0.6190 | 0.7998 | 0.7998 | 0.7998 | 0.7998 | |
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| 0.4949 | 3.0 | 2040 | 0.6024 | 0.8204 | 0.8204 | 0.8204 | 0.8204 | |
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### Framework versions |
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- Transformers 4.38.0 |
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- Pytorch 2.5.1+cu118 |
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- Datasets 3.2.0 |
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- Tokenizers 0.15.2 |
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