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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: fin_cate |
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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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# fin_cate |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0523 |
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- Accuracy: 0.9794 |
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- F1: 0.9794 |
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- Precision: 0.9794 |
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- Recall: 0.9794 |
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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: 64 |
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- eval_batch_size: 128 |
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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: 7 |
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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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| No log | 1.0 | 64 | 0.1458 | 0.9292 | 0.9292 | 0.9292 | 0.9292 | |
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| No log | 2.0 | 128 | 0.0591 | 0.9744 | 0.9744 | 0.9744 | 0.9744 | |
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| No log | 3.0 | 192 | 0.0488 | 0.9754 | 0.9754 | 0.9754 | 0.9754 | |
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| No log | 4.0 | 256 | 0.0487 | 0.9784 | 0.9788 | 0.9793 | 0.9784 | |
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| No log | 5.0 | 320 | 0.0500 | 0.9784 | 0.9784 | 0.9784 | 0.9784 | |
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| No log | 6.0 | 384 | 0.0506 | 0.9794 | 0.9794 | 0.9794 | 0.9794 | |
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| No log | 7.0 | 448 | 0.0523 | 0.9794 | 0.9794 | 0.9794 | 0.9794 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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