metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
model-index:
- name: Finetune-test3
results: []
Finetune-test3
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6143
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 |
---|---|---|---|
1.1515 | 0.9956 | 56 | 0.7617 |
0.7099 | 1.9911 | 112 | 0.6591 |
0.6427 | 2.9867 | 168 | 0.6336 |
0.5897 | 4.0 | 225 | 0.6145 |
0.5634 | 4.9956 | 281 | 0.6038 |
0.5328 | 5.9911 | 337 | 0.6003 |
0.5084 | 6.9867 | 393 | 0.6019 |
0.4793 | 8.0 | 450 | 0.6030 |
0.4718 | 8.9956 | 506 | 0.6088 |
0.4559 | 9.9556 | 560 | 0.6143 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.0.1+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1