mistral-7b-nli_cot
This model is a fine-tuned version of TheBloke/Mistral-7B-v0.1-GPTQ on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4930
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 11
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.4947 | 0.9996 | 598 | 0.4534 |
0.4418 | 1.9992 | 1196 | 0.4475 |
0.4262 | 2.9987 | 1794 | 0.4476 |
0.4125 | 4.0 | 2393 | 0.4499 |
0.4015 | 4.9996 | 2991 | 0.4552 |
0.3908 | 5.9992 | 3589 | 0.4591 |
0.3809 | 6.9987 | 4187 | 0.4653 |
0.3712 | 8.0 | 4786 | 0.4721 |
0.3635 | 8.9996 | 5384 | 0.4783 |
0.3562 | 9.9992 | 5982 | 0.4868 |
0.3496 | 10.9954 | 6578 | 0.4930 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.0.1+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for jd0g/Mistral-7B-NLI-v0.1
Base model
mistralai/Mistral-7B-v0.1
Quantized
TheBloke/Mistral-7B-v0.1-GPTQ