mistral-7b-instruct-lora-v3.0
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 2.2224
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 3
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 4 | 2.3675 |
No log | 2.0 | 8 | 2.3372 |
2.3612 | 3.0 | 12 | 2.3082 |
2.3612 | 4.0 | 16 | 2.2819 |
2.296 | 5.0 | 20 | 2.2598 |
2.296 | 6.0 | 24 | 2.2430 |
2.296 | 7.0 | 28 | 2.2317 |
2.2141 | 8.0 | 32 | 2.2254 |
2.2141 | 9.0 | 36 | 2.2229 |
2.252 | 10.0 | 40 | 2.2224 |
Framework versions
- PEFT 0.11.1
- Transformers 4.43.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
mistralai/Mistral-7B-Instruct-v0.2