coding_llamaduo_result3
This model is a fine-tuned version of google/gemma-7b on the chansung/merged_ds_coding dataset. It achieves the following results on the evaluation set:
- Loss: 1.7502
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.987 | 1.0 | 82 | 1.2808 |
| 0.6859 | 2.0 | 164 | 1.1719 |
| 0.5836 | 3.0 | 246 | 1.1480 |
| 0.5178 | 4.0 | 328 | 1.1717 |
| 0.4668 | 5.0 | 410 | 1.2044 |
| 0.3955 | 6.0 | 492 | 1.3252 |
| 0.3233 | 7.0 | 574 | 1.4225 |
| 0.2669 | 8.0 | 656 | 1.6119 |
| 0.2591 | 9.0 | 738 | 1.7353 |
| 0.2367 | 10.0 | 820 | 1.7502 |
Framework versions
- PEFT 0.7.1
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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