coding_llamaduo_60k
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: 1.6318
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: 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 |
---|---|---|---|
0.6618 | 1.0 | 252 | 1.2071 |
0.5731 | 2.0 | 504 | 1.1436 |
0.5198 | 3.0 | 756 | 1.1346 |
0.4783 | 4.0 | 1008 | 1.1536 |
0.4378 | 5.0 | 1260 | 1.2225 |
0.3836 | 6.0 | 1512 | 1.2893 |
0.3381 | 7.0 | 1764 | 1.4050 |
0.3043 | 8.0 | 2016 | 1.5185 |
0.2778 | 9.0 | 2268 | 1.6143 |
0.2748 | 10.0 | 2520 | 1.6318 |
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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Model tree for chansung/coding_llamaduo_60k
Base model
google/gemma-7b