FT-DS
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: 1.2844
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: 9
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 36
- 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 |
|---|---|---|---|
| 0.9542 | 1.0 | 1 | 1.8234 |
| 0.954 | 2.0 | 2 | 1.7674 |
| 0.9305 | 3.0 | 3 | 1.6566 |
| 0.8837 | 4.0 | 4 | 1.5636 |
| 0.843 | 5.0 | 5 | 1.4859 |
| 0.8086 | 6.0 | 6 | 1.4216 |
| 0.7804 | 7.0 | 7 | 1.3689 |
| 0.7578 | 8.0 | 8 | 1.3279 |
| 0.7405 | 9.0 | 9 | 1.2993 |
| 0.7283 | 10.0 | 10 | 1.2844 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for Karun-7/FT-DS
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ