mistral-7B-Instruct-prompt
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: 0.0962
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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 100
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.745 | 0.75 | 100 | 0.8404 |
0.5396 | 1.5 | 200 | 0.6313 |
0.3702 | 2.26 | 300 | 0.4994 |
0.3676 | 3.01 | 400 | 0.4106 |
0.3623 | 3.76 | 500 | 0.3409 |
0.2239 | 4.51 | 600 | 0.2893 |
0.1719 | 5.26 | 700 | 0.2405 |
0.1971 | 6.02 | 800 | 0.1866 |
0.1446 | 6.77 | 900 | 0.1591 |
0.1066 | 7.52 | 1000 | 0.1381 |
0.0866 | 8.27 | 1100 | 0.1193 |
0.0701 | 9.02 | 1200 | 0.1061 |
0.0641 | 9.77 | 1300 | 0.1017 |
0.0511 | 10.53 | 1400 | 0.0958 |
0.0407 | 11.28 | 1500 | 0.0963 |
0.0332 | 12.03 | 1600 | 0.0938 |
0.0268 | 12.78 | 1700 | 0.0952 |
0.0251 | 13.53 | 1800 | 0.0961 |
0.023 | 14.29 | 1900 | 0.0961 |
0.0219 | 15.04 | 2000 | 0.0962 |
Framework versions
- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for rreit/mistral-7B-Instruct-prompt
Base model
mistralai/Mistral-7B-Instruct-v0.2