coding_llamaduo_60k_v0.2
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: 1.3326
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 |
|---|---|---|---|
| 0.7499 | 1.0 | 126 | 1.2580 |
| 0.6058 | 2.0 | 252 | 1.1687 |
| 0.5571 | 3.0 | 378 | 1.1492 |
| 0.5118 | 4.0 | 504 | 1.1551 |
| 0.4711 | 5.0 | 630 | 1.1767 |
| 0.4287 | 6.0 | 756 | 1.1948 |
| 0.3943 | 7.0 | 882 | 1.2383 |
| 0.3612 | 8.0 | 1008 | 1.2904 |
| 0.3457 | 9.0 | 1134 | 1.3253 |
| 0.3328 | 10.0 | 1260 | 1.3326 |
Framework versions
- PEFT 0.7.1
- Transformers 4.40.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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google/gemma-7b