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gpt2_human
amalik27/gpt2_human
gpt2_human 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 12, 2023
- Updated
- Apr 12, 2023
- SHA
- fb4685bf
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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_human
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4323
- Accuracy: {'accuracy': 0.8127125850340136}
- F1: 0.8108
- Recall: 0.7227
- Precision: 0.8380
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 |
|---|---|---|---|---|---|---|---|
| 0.8137 | 1.0 | 10976 | 0.6581 | {'accuracy': 0.6217049319727891} | 0.6205 | 0.5507 | 0.5835 |
| 0.4538 | 2.0 | 21952 | 0.4323 | {'accuracy': 0.8127125850340136} | 0.8108 | 0.7227 | 0.8380 |
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 12, 2023
- Updated
- Apr 12, 2023