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
- Downloads last month
- 15
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for dvijay/mistral-alpaca-qlora
Base model
mistralai/Mistral-7B-v0.1