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---
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library_name: transformers
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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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model-index:
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- name: experiment_lr_20241215_145438-postcrash
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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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# experiment_lr_20241215_145438-postcrash
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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: 0.0166
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- Exact Match Accuracy: 0.5777
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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: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 7
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Exact Match Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------------------:|
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| 0.0725 | 1.0 | 2297 | 0.0720 | 0.0 |
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| 0.0661 | 2.0 | 4594 | 0.0607 | 0.0 |
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| 0.0422 | 3.0 | 6891 | 0.0356 | 0.0245 |
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| 0.0252 | 4.0 | 9188 | 0.0234 | 0.1441 |
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| 0.0193 | 5.0 | 11485 | 0.0185 | 0.4620 |
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| 0.0164 | 6.0 | 13782 | 0.0168 | 0.5711 |
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| 0.0158 | 7.0 | 16079 | 0.0166 | 0.5777 |
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### Framework versions
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- Transformers 4.47.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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