Mistral-QLoRA
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7970
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9181 | 0.8081 | 100 | 0.9132 |
| 0.7985 | 1.6162 | 200 | 0.8142 |
| 0.7637 | 2.4242 | 300 | 0.7970 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.1.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for dhanishetty/Mistral-QLoRA-TensorDock-Adapetrs
Base model
mistralai/Mistral-7B-v0.1
Finetuned
mistralai/Mistral-7B-Instruct-v0.1