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--- |
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license: mit |
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base_model: microsoft/deberta-v3-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: DeBERTa-finetuned-ner-S800 |
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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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# DeBERTa-finetuned-ner-S800 |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0606 |
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- Precision: 0.6730 |
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- Recall: 0.7899 |
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- F1: 0.7268 |
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- Accuracy: 0.9783 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 55 | 0.0744 | 0.5840 | 0.6527 | 0.6164 | 0.9703 | |
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| No log | 2.0 | 110 | 0.0639 | 0.6332 | 0.7689 | 0.6945 | 0.9764 | |
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| No log | 3.0 | 165 | 0.0585 | 0.6424 | 0.7801 | 0.7046 | 0.9766 | |
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| No log | 4.0 | 220 | 0.0581 | 0.6754 | 0.7955 | 0.7305 | 0.9785 | |
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| No log | 5.0 | 275 | 0.0606 | 0.6730 | 0.7899 | 0.7268 | 0.9783 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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