distilgpt2-lora-text-classification
This model is a fine-tuned version of distilbert/distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 6.5596
- Rougel F1: 0.0
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rougel F1 |
|---|---|---|---|---|
| No log | 1.0 | 83 | 7.1013 | 0.0 |
| No log | 2.0 | 166 | 6.9855 | 0.0 |
| No log | 3.0 | 249 | 6.8850 | 0.0 |
| No log | 4.0 | 332 | 6.7975 | 0.0 |
| No log | 5.0 | 415 | 6.7247 | 0.0 |
| No log | 6.0 | 498 | 6.6657 | 0.0 |
| 7.0748 | 7.0 | 581 | 6.6194 | 0.0 |
| 7.0748 | 8.0 | 664 | 6.5859 | 0.0 |
| 7.0748 | 9.0 | 747 | 6.5662 | 0.0 |
| 7.0748 | 10.0 | 830 | 6.5596 | 0.0 |
Framework versions
- PEFT 0.14.0
- Transformers 4.43.4
- Pytorch 2.6.0
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
distilbert/distilgpt2