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---
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library_name: transformers
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license: mit
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base_model: KoNqUeRoR3891/HW2-supervised
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tags:
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- trl
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- reward-trainer
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- generated_from_trainer
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datasets:
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- piqa
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metrics:
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- accuracy
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model-index:
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- name: HW2-reward
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: piqa
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type: piqa
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config: plain_text
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split: train
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args: plain_text
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.640818858560794
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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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# HW2-reward
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This model is a fine-tuned version of [KoNqUeRoR3891/HW2-supervised](https://huggingface.co/KoNqUeRoR3891/HW2-supervised) on the piqa dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7024
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- Accuracy: 0.6408
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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: 5e-05
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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: 3
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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 | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.6793 | 1.0 | 3626 | 0.6733 | 0.5782 |
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| 0.6767 | 2.0 | 7252 | 0.6590 | 0.6210 |
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| 0.5686 | 3.0 | 10878 | 0.7024 | 0.6408 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.0+cu118
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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