metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
model-index:
- name: mistral-finetune
results: []
mistral-finetune
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6868
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2888 | 0.9231 | 3 | 1.9164 |
| 2.2101 | 1.8462 | 6 | 1.8524 |
| 2.1445 | 2.7692 | 9 | 1.8134 |
| 1.5809 | 4.0 | 13 | 1.7771 |
| 2.0793 | 4.9231 | 16 | 1.7462 |
| 2.033 | 5.8462 | 19 | 1.7224 |
| 2.0251 | 6.7692 | 22 | 1.7058 |
| 1.4839 | 8.0 | 26 | 1.6924 |
| 1.9771 | 8.9231 | 29 | 1.6874 |
| 1.3942 | 9.2308 | 30 | 1.6868 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.1.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1