gemma-2b-dolly-qa
This model is a fine-tuned version of google/gemma-2b on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 2.0215
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
databricks/databricks-dolly-15k
Training Hardware
This model was trained using Intel(R) Data Center GPU Max 1100
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 1480
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.9198 | 1.64 | 100 | 2.5675 |
2.437 | 3.28 | 200 | 2.2818 |
2.2514 | 4.92 | 300 | 2.1677 |
2.1587 | 6.56 | 400 | 2.1038 |
2.116 | 8.2 | 500 | 2.0741 |
2.0794 | 9.84 | 600 | 2.0576 |
2.0663 | 11.48 | 700 | 2.0467 |
2.0494 | 13.11 | 800 | 2.0394 |
2.0449 | 14.75 | 900 | 2.0336 |
2.0336 | 16.39 | 1000 | 2.0293 |
2.0281 | 18.03 | 1100 | 2.0262 |
2.0172 | 19.67 | 1200 | 2.0240 |
2.0227 | 21.31 | 1300 | 2.0227 |
2.0128 | 22.95 | 1400 | 2.0215 |
Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.0.1a0+cxx11.abi
- Datasets 2.18.0
- Tokenizers 0.15.2
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