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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
model-index:
- name: Finetune-test4
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Finetune-test4
This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1223
## 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.767 | 0.9956 | 56 | 0.5333 |
| 0.4313 | 1.9911 | 112 | 0.4449 |
| 0.3107 | 2.9867 | 168 | 0.4640 |
| 0.2198 | 4.0 | 225 | 0.5196 |
| 0.1633 | 4.9956 | 281 | 0.5811 |
| 0.1209 | 5.9911 | 337 | 0.6468 |
| 0.0944 | 6.9867 | 393 | 0.6891 |
| 0.0745 | 8.0 | 450 | 0.7297 |
| 0.064 | 8.9956 | 506 | 0.7844 |
| 0.0557 | 9.9911 | 562 | 0.8384 |
| 0.0489 | 10.9867 | 618 | 0.8632 |
| 0.0433 | 12.0 | 675 | 0.9223 |
| 0.0413 | 12.9956 | 731 | 0.9526 |
| 0.0389 | 13.9911 | 787 | 0.9552 |
| 0.0375 | 14.9867 | 843 | 1.0303 |
| 0.0355 | 16.0 | 900 | 1.0489 |
| 0.0355 | 16.9956 | 956 | 1.0804 |
| 0.0347 | 17.9911 | 1012 | 1.0983 |
| 0.0341 | 18.9867 | 1068 | 1.1147 |
| 0.0328 | 19.9111 | 1120 | 1.1223 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.0.1+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1 |