---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Mistral-7B-v0.1-GPTQ
model-index:
- name: mistral-7b-nli_cot_qkv
  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. -->

# mistral-7b-nli_cot_qkv

This model is a fine-tuned version of [TheBloke/Mistral-7B-v0.1-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-v0.1-GPTQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7749

## 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: 8
- 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: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.426         | 0.9998  | 1196  | 0.4255          |
| 0.3664        | 1.9996  | 2392  | 0.4365          |
| 0.3221        | 2.9994  | 3588  | 0.4455          |
| 0.2804        | 4.0     | 4785  | 0.4577          |
| 0.2403        | 4.9998  | 5981  | 0.4719          |
| 0.2001        | 5.9996  | 7177  | 0.4948          |
| 0.1643        | 6.9994  | 8373  | 0.5278          |
| 0.1305        | 8.0     | 9570  | 0.5634          |
| 0.1011        | 8.9998  | 10766 | 0.6095          |
| 0.0768        | 9.9996  | 11962 | 0.6621          |
| 0.0577        | 10.9994 | 13158 | 0.7225          |
| 0.0445        | 11.9975 | 14352 | 0.7749          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.0.1+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1