peft safetensors generated_from_trainer base_model:mistralai/Mixtral-8x7B-v0.1 license:apache-2.0 region:us
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mixtral-8x7B-v0.1
model-index:
- name: mixtral_no_robots_secondtry
  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. -->

# mixtral_no_robots_secondtry

This model is a fine-tuned version of [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9807

## 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: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.0635        | 0.02  | 1000  | 1.1332          |
| 0.9311        | 0.03  | 2000  | 1.1109          |
| 0.9417        | 0.05  | 3000  | 1.0926          |
| 1.0411        | 0.06  | 4000  | 1.0809          |
| 0.9516        | 0.08  | 5000  | 1.0786          |
| 1.0107        | 0.09  | 6000  | 1.0726          |
| 1.0698        | 0.11  | 7000  | 1.0666          |
| 1.1083        | 0.13  | 8000  | 1.0638          |
| 0.9148        | 0.14  | 9000  | 1.0589          |
| 0.957         | 0.16  | 10000 | 1.0565          |
| 1.0063        | 0.17  | 11000 | 1.0531          |
| 0.9831        | 0.19  | 12000 | 1.0509          |
| 1.0826        | 0.2   | 13000 | 1.0490          |
| 0.9598        | 0.22  | 14000 | 1.0518          |
| 0.8066        | 0.23  | 15000 | 1.0453          |
| 0.8795        | 0.25  | 16000 | 1.0431          |
| 1.1402        | 0.27  | 17000 | 1.0442          |
| 1.0652        | 0.28  | 18000 | 1.0428          |
| 0.93          | 0.3   | 19000 | 1.0371          |
| 0.9727        | 0.31  | 20000 | 1.0344          |
| 1.0753        | 0.33  | 21000 | 1.0339          |
| 0.9498        | 0.34  | 22000 | 1.0303          |
| 0.6971        | 0.36  | 23000 | 1.0316          |
| 0.9259        | 0.38  | 24000 | 1.0298          |
| 1.0359        | 0.39  | 25000 | 1.0284          |
| 1.1883        | 0.41  | 26000 | 1.0273          |
| 0.8642        | 0.42  | 27000 | 1.0250          |
| 0.9147        | 0.44  | 28000 | 1.0226          |
| 0.7824        | 0.45  | 29000 | 1.0237          |
| 0.8319        | 0.47  | 30000 | 1.0219          |
| 0.9443        | 0.49  | 31000 | 1.0190          |
| 0.9103        | 0.5   | 32000 | 1.0166          |
| 0.8903        | 0.52  | 33000 | 1.0149          |
| 1.0509        | 0.53  | 34000 | 1.0148          |
| 1.0008        | 0.55  | 35000 | 1.0151          |
| 0.778         | 0.56  | 36000 | 1.0106          |
| 0.7957        | 0.58  | 37000 | 1.0090          |
| 0.8679        | 0.6   | 38000 | 1.0085          |
| 1.064         | 0.61  | 39000 | 1.0064          |
| 0.823         | 0.63  | 40000 | 1.0061          |
| 0.9117        | 0.64  | 41000 | 1.0047          |
| 0.8284        | 0.66  | 42000 | 1.0019          |
| 0.9345        | 0.67  | 43000 | 1.0012          |
| 0.9854        | 0.69  | 44000 | 1.0004          |
| 0.7631        | 0.7   | 45000 | 0.9989          |
| 0.7189        | 0.72  | 46000 | 0.9979          |
| 0.9386        | 0.74  | 47000 | 0.9952          |
| 1.011         | 0.75  | 48000 | 0.9943          |
| 0.9627        | 0.77  | 49000 | 0.9941          |
| 1.1317        | 0.78  | 50000 | 0.9923          |
| 1.0506        | 0.8   | 51000 | 0.9912          |
| 0.8596        | 0.81  | 52000 | 0.9894          |
| 0.9702        | 0.83  | 53000 | 0.9889          |
| 1.0198        | 0.85  | 54000 | 0.9875          |
| 1.1125        | 0.86  | 55000 | 0.9862          |
| 0.9356        | 0.88  | 56000 | 0.9862          |
| 0.7212        | 0.89  | 57000 | 0.9852          |
| 0.974         | 0.91  | 58000 | 0.9843          |
| 0.9369        | 0.92  | 59000 | 0.9829          |
| 0.938         | 0.94  | 60000 | 0.9826          |
| 0.8011        | 0.96  | 61000 | 0.9818          |
| 0.7937        | 0.97  | 62000 | 0.9811          |
| 0.9679        | 0.99  | 63000 | 0.9807          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0