---
tags:
- generated_from_trainer
model-index:
- name: lora-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)
# lora-out

This model was trained from scratch on the [TokenBender/roleplay_alpaca](https://huggingface.co/datasets/TokenBender/roleplay_alpaca) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2973

## Model description

Dataset trained on [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.00065
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 10
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5404        | 0.03  | 20   | 1.2764          |
| 1.4523        | 0.06  | 40   | 1.2571          |
| 1.5608        | 0.09  | 60   | 1.2465          |
| 1.5921        | 0.12  | 80   | 1.2575          |
| 1.6043        | 0.15  | 100  | 1.2432          |
| 1.5496        | 0.18  | 120  | 1.2504          |
| 1.348         | 0.21  | 140  | 1.2452          |
| 1.4638        | 0.24  | 160  | 1.2661          |
| 1.5733        | 0.27  | 180  | 1.2548          |
| 1.5397        | 0.3   | 200  | 1.2674          |
| 1.6154        | 0.33  | 220  | 1.2626          |
| 1.5058        | 0.36  | 240  | 1.2672          |
| 1.3974        | 0.4   | 260  | 1.2659          |
| 1.6654        | 0.43  | 280  | 1.2648          |
| 1.8051        | 0.46  | 300  | 1.2585          |
| 1.7487        | 0.49  | 320  | 1.2736          |
| 1.3612        | 0.52  | 340  | 1.2717          |
| 1.5048        | 0.55  | 360  | 1.2809          |
| 1.7134        | 0.58  | 380  | 1.2885          |
| 1.5524        | 0.61  | 400  | 1.2805          |
| 1.3705        | 0.64  | 420  | 1.2860          |
| 1.4335        | 0.67  | 440  | 1.2896          |
| 1.3642        | 0.7   | 460  | 1.2911          |
| 1.6546        | 0.73  | 480  | 1.2888          |
| 1.5345        | 0.76  | 500  | 1.2973          |
| 1.5968        | 0.79  | 520  | 1.2885          |
| 1.5694        | 0.82  | 540  | 1.2939          |
| 1.5474        | 0.85  | 560  | 1.2892          |
| 1.6981        | 0.88  | 580  | 1.2949          |
| 1.5451        | 0.91  | 600  | 1.2886          |
| 1.5845        | 0.94  | 620  | 1.2941          |
| 1.5143        | 0.97  | 640  | 1.2973          |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0

If you want to support me, you can [here](https://ko-fi.com/undiai).