llama3-8b-coding-gpt4o-100k
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the llama-duo/synth_coding_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 1.5174
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: 0.002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 |
|---|---|---|---|
| 0.4861 | 1.0 | 135 | 1.2495 |
| 0.458 | 2.0 | 270 | 1.2390 |
| 0.4423 | 3.0 | 405 | 1.2549 |
| 0.4244 | 4.0 | 540 | 1.2665 |
| 0.4051 | 5.0 | 675 | 1.2714 |
| 0.3815 | 6.0 | 810 | 1.2959 |
| 0.3546 | 7.0 | 945 | 1.3560 |
| 0.3233 | 8.0 | 1080 | 1.4125 |
| 0.2969 | 9.0 | 1215 | 1.4809 |
| 0.2818 | 10.0 | 1350 | 1.5174 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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