Mistral-7B-Instruct-v0.2-finetuned-justification-v01
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7757
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.4434 | 1.0 | 169 | 1.5820 |
1.5221 | 2.0 | 338 | 1.5810 |
0.824 | 3.0 | 507 | 1.7089 |
0.9674 | 4.0 | 676 | 1.8947 |
0.6174 | 5.0 | 845 | 2.0892 |
0.4672 | 6.0 | 1014 | 2.2550 |
0.215 | 7.0 | 1183 | 2.4206 |
0.1316 | 8.0 | 1352 | 2.5481 |
0.0846 | 9.0 | 1521 | 2.7126 |
0.0696 | 10.0 | 1690 | 2.7757 |
Framework versions
- PEFT 0.10.0
- Transformers 4.36.2
- Pytorch 2.2.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.2
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