fine-tuned
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7251
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0421 | 0.7273 | 2 | 0.9421 |
| 0.6584 | 1.8182 | 5 | 0.8734 |
| 0.6334 | 2.9091 | 8 | 0.8160 |
| 0.5834 | 4.0 | 11 | 0.7785 |
| 0.8285 | 4.7273 | 13 | 0.7600 |
| 0.5284 | 5.8182 | 16 | 0.7385 |
| 0.5488 | 6.9091 | 19 | 0.7266 |
| 0.4193 | 7.2727 | 20 | 0.7251 |
Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for justnavneet/fine-tuned
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ