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LLM
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1197
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 |
---|---|---|---|
2.0514 | 0.92 | 6 | 1.5349 |
1.1699 | 2.0 | 13 | 0.9568 |
0.8058 | 2.92 | 19 | 0.4997 |
0.2976 | 4.0 | 26 | 0.1891 |
0.1737 | 4.92 | 32 | 0.1461 |
0.1267 | 6.0 | 39 | 0.1334 |
0.1339 | 6.92 | 45 | 0.1235 |
0.108 | 8.0 | 52 | 0.1203 |
0.1233 | 8.92 | 58 | 0.1198 |
0.0865 | 9.23 | 60 | 0.1197 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for george2704/LLM
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ