---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: qlora-out
  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. -->

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# qlora-out

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5840

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 300
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.767         | 0.24  | 20   | 0.6343          |
| 0.6849        | 0.48  | 40   | 0.5669          |
| 0.6761        | 0.72  | 60   | 0.5247          |
| 0.5534        | 0.96  | 80   | 0.5044          |
| 0.4757        | 1.2   | 100  | 0.5023          |
| 0.5158        | 1.44  | 120  | 0.4883          |
| 0.5414        | 1.68  | 140  | 0.4809          |
| 0.4715        | 1.92  | 160  | 0.4748          |
| 0.4037        | 2.16  | 180  | 0.4873          |
| 0.4213        | 2.4   | 200  | 0.5194          |
| 0.2988        | 2.64  | 220  | 0.6278          |
| 0.3477        | 2.88  | 240  | 0.5840          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1