gemma-sft-qlora
This model is a fine-tuned version of google/gemma-7b on the satpalsr/hindi-sample dataset. It achieves the following results on the evaluation set:
- Loss: 0.6385
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1537 | 0.99 | 94 | 1.0988 |
| 0.9028 | 1.99 | 189 | 0.8056 |
| 0.6553 | 2.99 | 284 | 0.6577 |
| 0.4936 | 3.96 | 376 | 0.6385 |
Framework versions
- PEFT 0.7.1
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
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google/gemma-7b