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HW2-reward
KoNqUeRoR3891/HW2-reward
HW2-reward is a text classification model from KoNqUeRoR3891. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- gpt2
- Access
- Public
- Created
- Sep 3, 2024
- Updated
- Sep 3, 2024
- SHA
- ef86cc9f
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Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
HW2-reward
This model is a fine-tuned version of KoNqUeRoR3891/HW2-supervised on the piqa dataset. It achieves the following results on the evaluation set:
- Loss: 0.7024
- Accuracy: 0.6408
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6793 | 1.0 | 3626 | 0.6733 | 0.5782 |
| 0.6767 | 2.0 | 7252 | 0.6590 | 0.6210 |
| 0.5686 | 3.0 | 10878 | 0.7024 | 0.6408 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- gpt2
- License
- mit
- Created
- Sep 3, 2024
- Updated
- Sep 3, 2024