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gpt2_combined
amalik27/gpt2_combined
gpt2_combined is a text classification model from amalik27. 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
- Apr 11, 2023
- Updated
- Apr 12, 2023
- SHA
- 2b50321a
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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. -->
gpt2_combined
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3831
- Accuracy: {'accuracy': 0.8384363566339302}
- F1: 0.8383
- Recall: 0.8626
- Precision: 0.8237
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: 0.001
- 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.8388 | 1.0 | 12117 | 0.7077 | {'accuracy': 0.6159734257654534} | 0.5569 | 0.2514 | 0.9377 |
| 0.3882 | 2.0 | 24234 | 0.3831 | {'accuracy': 0.8384363566339302} | 0.8383 | 0.8626 | 0.8237 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- gpt2
- License
- mit
- Created
- Apr 11, 2023
- Updated
- Apr 12, 2023