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gpt2-finetuned-PRC
agarc15/gpt2-finetuned-PRC
gpt2-finetuned-PRC is a text classification model from agarc15. 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
- Aug 21, 2023
- Updated
- Aug 22, 2023
- SHA
- 28b3c7d6
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Base models
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-finetuned-PRC
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4564
- Accuracy: 0.8711
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 391 | 0.5038 | 0.8420 |
| 0.7758 | 2.0 | 782 | 0.4486 | 0.8629 |
| 0.4031 | 3.0 | 1173 | 0.4664 | 0.8678 |
| 0.3225 | 4.0 | 1564 | 0.4564 | 0.8711 |
| 0.3225 | 5.0 | 1955 | 0.4637 | 0.8693 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- gpt2
- License
- mit
- Created
- Aug 21, 2023
- Updated
- Aug 22, 2023