---
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: 1.2423

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5123        | 0.01  | 1    | 1.5038          |
| 1.3662        | 0.06  | 5    | 1.4103          |
| 1.1836        | 0.11  | 10   | 1.3055          |
| 1.2761        | 0.17  | 15   | 1.2810          |
| 1.1779        | 0.22  | 20   | 1.2696          |
| 1.1242        | 0.28  | 25   | 1.2642          |
| 1.2414        | 0.33  | 30   | 1.2588          |
| 1.1382        | 0.39  | 35   | 1.2555          |
| 1.2094        | 0.45  | 40   | 1.2520          |
| 1.1049        | 0.5   | 45   | 1.2504          |
| 1.1709        | 0.56  | 50   | 1.2487          |
| 1.0981        | 0.61  | 55   | 1.2463          |
| 1.1902        | 0.67  | 60   | 1.2446          |
| 1.1526        | 0.72  | 65   | 1.2446          |
| 1.1319        | 0.78  | 70   | 1.2440          |
| 1.1913        | 0.84  | 75   | 1.2430          |
| 1.1875        | 0.89  | 80   | 1.2424          |
| 1.1454        | 0.95  | 85   | 1.2423          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0