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gmra_model_gpt2_10082023T191709
samaksh-khatri-crest-data/gmra_model_gpt2_10082023T191709
gmra_model_gpt2_10082023T191709 is a text classification model from samaksh-khatri-crest-data. 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 10, 2023
- Updated
- Aug 10, 2023
- SHA
- 8ecf22a8
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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. -->
gmra_model_gpt2_10082023T191709
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5190
- Accuracy: 0.9132
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: 0.002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | 124 | 0.5084 | 0.8423 |
| No log | 2.0 | 249 | 0.3607 | 0.8886 |
| No log | 3.0 | 373 | 0.4232 | 0.9062 |
| No log | 4.0 | 498 | 0.4970 | 0.9056 |
| 0.367 | 4.98 | 620 | 0.5190 | 0.9132 |
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 10, 2023
- Updated
- Aug 10, 2023