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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: results |
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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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# results |
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the KMC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0556 |
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- Accuracy: 0.8722 |
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- F1: 0.8849 |
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- Precision: 0.8950 |
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- Recall: 0.8750 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 5 |
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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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| 0.0894 | 1.0 | 1633 | 0.0817 | 0.7508 | 0.8072 | 0.8774 | 0.7474 | |
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| 0.059 | 2.0 | 3266 | 0.0620 | 0.8264 | 0.8520 | 0.8815 | 0.8243 | |
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| 0.0429 | 3.0 | 4899 | 0.0531 | 0.8563 | 0.8751 | 0.8947 | 0.8563 | |
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| 0.032 | 4.0 | 6532 | 0.0547 | 0.8704 | 0.8838 | 0.8976 | 0.8705 | |
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| 0.0253 | 5.0 | 8165 | 0.0556 | 0.8722 | 0.8849 | 0.8950 | 0.8750 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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