metadata
library_name: peft
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.3
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
model-index:
- name: mistral-qlora_v2
results: []
mistral-qlora_v2
This model is a fine-tuned version of mistralai/Mistral-7B-v0.3 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 1.2705
- Mean Token Accuracy: 0.6893
- Num Tokens: 896294
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Token Accuracy | Num Tokens |
|---|---|---|---|---|---|
| 1.4786 | 0.3077 | 8 | 1.3624 | 0.6773 | 896294 |
| 1.3292 | 0.6154 | 16 | 1.3184 | 0.6833 | 896294 |
| 1.3818 | 0.9231 | 24 | 1.2928 | 0.6865 | 896294 |
| 1.2772 | 1.2308 | 32 | 1.2793 | 0.6878 | 896294 |
| 1.3531 | 1.5385 | 40 | 1.2725 | 0.6890 | 896294 |
| 1.2099 | 1.8462 | 48 | 1.2705 | 0.6893 | 896294 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.8.0+cu126
- Datasets 2.20.0
- Tokenizers 0.19.1