mistral_7b_0_3-coding-gpt4o-100k2
This model is a fine-tuned version of mistralai/Mistral-7B-v0.3 on the llama-duo/synth_coding_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 1.1573
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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 |
|---|---|---|---|
| 0.419 | 0.9992 | 640 | 1.0503 |
| 0.3829 | 2.0 | 1281 | 1.0418 |
| 0.3774 | 2.9992 | 1921 | 1.0361 |
| 0.355 | 4.0 | 2562 | 1.0419 |
| 0.3413 | 4.9992 | 3202 | 1.0548 |
| 0.318 | 6.0 | 3843 | 1.0761 |
| 0.3056 | 6.9992 | 4483 | 1.1023 |
| 0.2857 | 8.0 | 5124 | 1.1256 |
| 0.2732 | 8.9992 | 5764 | 1.1472 |
| 0.2714 | 9.9922 | 6400 | 1.1573 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
mistralai/Mistral-7B-v0.3