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--- |
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license: mit |
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base_model: roberta-base |
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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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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7451 |
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- Accuracy: {'accuracy': 0.933} |
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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: 10 |
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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 | 0.3071 | {'accuracy': 0.919} | |
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| 0.3665 | 2.0 | 500 | 0.3954 | {'accuracy': 0.922} | |
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| 0.3665 | 3.0 | 750 | 0.3318 | {'accuracy': 0.937} | |
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| 0.1483 | 4.0 | 1000 | 0.5179 | {'accuracy': 0.942} | |
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| 0.1483 | 5.0 | 1250 | 0.5112 | {'accuracy': 0.933} | |
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| 0.0829 | 6.0 | 1500 | 0.5775 | {'accuracy': 0.936} | |
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| 0.0829 | 7.0 | 1750 | 0.6473 | {'accuracy': 0.931} | |
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| 0.019 | 8.0 | 2000 | 0.6950 | {'accuracy': 0.937} | |
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| 0.019 | 9.0 | 2250 | 0.7328 | {'accuracy': 0.931} | |
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| 0.008 | 10.0 | 2500 | 0.7451 | {'accuracy': 0.933} | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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