ERC_SUMMARY_gemma_peft
This model is a fine-tuned version of google/gemma-7b-it on the ArunaMak/ERC_summary dataset. It achieves the following results on the evaluation set:
- Loss: 1.5364
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: 1e-05
- 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: cosine
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.3768 | 0.9921 | 94 | 4.8155 |
| 1.6402 | 1.9947 | 189 | 1.6594 |
| 1.3945 | 2.9974 | 284 | 1.5666 |
| 1.3478 | 4.0 | 379 | 1.5460 |
| 1.3085 | 4.9921 | 473 | 1.5388 |
| 1.1856 | 5.9525 | 564 | 1.5364 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.0.dev0
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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