ft-google-gemma-2b-it-qlora
This model is a fine-tuned version of google/gemma-2b-it on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.3317
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.1202 | 3.0 | 3 | 3.0015 |
0.0529 | 6.0 | 6 | 3.0532 |
0.0148 | 9.0 | 9 | 3.3317 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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