qlora-out
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3313
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.4833 | 0.13 | 1 | 2.5152 |
| 2.5615 | 0.26 | 2 | 2.5078 |
| 2.4965 | 0.39 | 3 | 2.4691 |
| 2.3902 | 0.52 | 4 | 2.4249 |
| 2.3629 | 0.65 | 5 | 2.3824 |
| 2.2324 | 0.77 | 6 | 2.3441 |
| 2.1907 | 0.9 | 7 | 2.3313 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
mistralai/Mistral-7B-v0.1