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--- |
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base_model: roberta-base |
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library_name: peft |
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license: mit |
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metrics: |
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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-lora-text-classification |
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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-lora-text-classification |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8264 |
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- Accuracy: {'accuracy': 0.862} |
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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: 0.001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:-------------------:| |
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| No log | 1.0 | 250 | 0.4008 | {'accuracy': 0.82} | |
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| 0.6294 | 2.0 | 500 | 0.6326 | {'accuracy': 0.84} | |
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| 0.6294 | 3.0 | 750 | 0.6141 | {'accuracy': 0.87} | |
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| 0.3802 | 4.0 | 1000 | 1.2677 | {'accuracy': 0.82} | |
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| 0.3802 | 5.0 | 1250 | 0.8264 | {'accuracy': 0.862} | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
