mistral-sql-finetune
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0305
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: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 300
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.1899 | 0.17 | 25 | 0.3116 |
0.1795 | 0.33 | 50 | 0.1088 |
0.0819 | 0.5 | 75 | 0.0425 |
0.0453 | 0.67 | 100 | 0.0419 |
0.0534 | 0.83 | 125 | 0.0382 |
0.0338 | 1.0 | 150 | 0.0315 |
0.0358 | 1.17 | 175 | 0.0345 |
0.0336 | 1.33 | 200 | 0.0334 |
0.0401 | 1.5 | 225 | 0.0322 |
0.0326 | 1.67 | 250 | 0.0308 |
0.0396 | 1.83 | 275 | 0.0309 |
0.0307 | 2.0 | 300 | 0.0305 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for baltop/zwave-dbgatekeeper-v0.3
Base model
mistralai/Mistral-7B-Instruct-v0.2