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--- |
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base_model: FacebookAI/roberta-base |
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library_name: peft |
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license: mit |
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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: roberta-base-ner-qlorafinetune-runs-128-256 |
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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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# roberta-base-ner-qlorafinetune-runs-128-256 |
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This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1219 |
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- Precision: 0.9390 |
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- Recall: 0.9644 |
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- F1: 0.9515 |
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- Accuracy: 0.9817 |
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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: 3.0 |
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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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| 0.1187 | 1.0 | 2643 | 0.1579 | 0.9680 | 0.9512 | 0.9595 | 0.9749 | |
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| 0.1311 | 2.0 | 5286 | 0.1306 | 0.9290 | 0.9607 | 0.9446 | 0.9793 | |
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| 0.0897 | 3.0 | 7929 | 0.1219 | 0.9390 | 0.9644 | 0.9515 | 0.9817 | |
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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 |
