mistral-alpaca-qlora
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the mhenrichsen/alpaca_2k_test dataset. It achieves the following results on the evaluation set:
- Loss: 1.3095
Model description
Standard mistral 7B fine tuned with alpaca format.
Intended uses & limitations
More information needed
Training and evaluation data
mhenrichsen/alpaca_2k_test
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
5.5317 | 0.07 | 1 | 5.2182 |
5.438 | 0.2 | 3 | 4.7897 |
4.1476 | 0.4 | 6 | 3.4313 |
3.2037 | 0.6 | 9 | 2.8663 |
2.7895 | 0.8 | 12 | 2.5112 |
2.3139 | 1.0 | 15 | 2.1467 |
2.1672 | 1.2 | 18 | 1.8620 |
1.9095 | 1.4 | 21 | 1.6519 |
1.5397 | 1.6 | 24 | 1.5429 |
1.6327 | 1.8 | 27 | 1.4518 |
1.3676 | 2.0 | 30 | 1.3892 |
1.3906 | 2.2 | 33 | 1.3531 |
1.4096 | 2.4 | 36 | 1.3314 |
1.3278 | 2.6 | 39 | 1.3165 |
1.3007 | 2.8 | 42 | 1.3107 |
1.2848 | 3.0 | 45 | 1.3095 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for dvijay/mistral-alpaca-qlora
Base model
mistralai/Mistral-7B-v0.1