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--- |
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base_model: distilbert-base-uncased |
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library_name: peft |
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license: apache-2.0 |
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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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tags: |
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- generated_from_trainer |
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model-index: |
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- name: distilbert-ner-lorafinetune-runs-v1 |
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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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# distilbert-ner-lorafinetune-runs-v1 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0735 |
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- Precision: 0.9638 |
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- Recall: 0.9778 |
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- F1: 0.9708 |
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- Accuracy: 0.9888 |
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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: 0.0004 |
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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: 4 |
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- mixed_precision_training: Native AMP |
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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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| 0.0808 | 1.0 | 2643 | 0.1186 | 0.9399 | 0.9629 | 0.9513 | 0.9818 | |
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| 0.0648 | 2.0 | 5286 | 0.0807 | 0.9556 | 0.9736 | 0.9645 | 0.9868 | |
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| 0.0366 | 3.0 | 7929 | 0.0761 | 0.9611 | 0.9770 | 0.9690 | 0.9883 | |
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| 0.0306 | 4.0 | 10572 | 0.0735 | 0.9638 | 0.9778 | 0.9708 | 0.9888 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.3 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
