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

# results_mixtral_sft

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: 0.2331

## 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: 2e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 1    | 2.4533          |
| No log        | 2.0   | 2    | 2.4493          |
| No log        | 3.0   | 3    | 2.4436          |
| No log        | 4.0   | 4    | 2.4352          |
| No log        | 5.0   | 5    | 2.4249          |
| No log        | 6.0   | 6    | 2.4215          |
| No log        | 7.0   | 7    | 2.4047          |
| No log        | 8.0   | 8    | 2.3842          |
| No log        | 9.0   | 9    | 2.3561          |
| No log        | 10.0  | 10   | 2.3295          |
| No log        | 11.0  | 11   | 2.3004          |
| No log        | 12.0  | 12   | 2.2563          |
| No log        | 13.0  | 13   | 2.2130          |
| No log        | 14.0  | 14   | 2.1715          |
| No log        | 15.0  | 15   | 2.1203          |
| No log        | 16.0  | 16   | 2.0893          |
| No log        | 17.0  | 17   | 2.0458          |
| No log        | 18.0  | 18   | 1.9937          |
| No log        | 19.0  | 19   | 1.9469          |
| No log        | 20.0  | 20   | 1.9085          |
| No log        | 21.0  | 21   | 1.9413          |
| No log        | 22.0  | 22   | 1.8690          |
| No log        | 23.0  | 23   | 1.8139          |
| No log        | 24.0  | 24   | 1.7389          |
| 1.0996        | 25.0  | 25   | 1.6836          |
| 1.0996        | 26.0  | 26   | 1.6236          |
| 1.0996        | 27.0  | 27   | 1.5705          |
| 1.0996        | 28.0  | 28   | 1.5261          |
| 1.0996        | 29.0  | 29   | 1.4790          |
| 1.0996        | 30.0  | 30   | 1.4240          |
| 1.0996        | 31.0  | 31   | 1.3674          |
| 1.0996        | 32.0  | 32   | 1.3182          |
| 1.0996        | 33.0  | 33   | 1.2769          |
| 1.0996        | 34.0  | 34   | 1.2321          |
| 1.0996        | 35.0  | 35   | 1.1885          |
| 1.0996        | 36.0  | 36   | 1.1445          |
| 1.0996        | 37.0  | 37   | 1.0878          |
| 1.0996        | 38.0  | 38   | 1.0237          |
| 1.0996        | 39.0  | 39   | 0.9748          |
| 1.0996        | 40.0  | 40   | 0.9294          |
| 1.0996        | 41.0  | 41   | 0.8806          |
| 1.0996        | 42.0  | 42   | 0.8457          |
| 1.0996        | 43.0  | 43   | 0.7969          |
| 1.0996        | 44.0  | 44   | 0.7599          |
| 1.0996        | 45.0  | 45   | 0.7189          |
| 1.0996        | 46.0  | 46   | 0.6952          |
| 1.0996        | 47.0  | 47   | 0.6570          |
| 1.0996        | 48.0  | 48   | 0.6316          |
| 1.0996        | 49.0  | 49   | 0.6212          |
| 0.548         | 50.0  | 50   | 0.5764          |
| 0.548         | 51.0  | 51   | 0.5113          |
| 0.548         | 52.0  | 52   | 0.4868          |
| 0.548         | 53.0  | 53   | 0.4585          |
| 0.548         | 54.0  | 54   | 0.4334          |
| 0.548         | 55.0  | 55   | 0.4208          |
| 0.548         | 56.0  | 56   | 0.4087          |
| 0.548         | 57.0  | 57   | 0.3945          |
| 0.548         | 58.0  | 58   | 0.3722          |
| 0.548         | 59.0  | 59   | 0.3588          |
| 0.548         | 60.0  | 60   | 0.3414          |
| 0.548         | 61.0  | 61   | 0.3235          |
| 0.548         | 62.0  | 62   | 0.3157          |
| 0.548         | 63.0  | 63   | 0.3050          |
| 0.548         | 64.0  | 64   | 0.2969          |
| 0.548         | 65.0  | 65   | 0.2893          |
| 0.548         | 66.0  | 66   | 0.2802          |
| 0.548         | 67.0  | 67   | 0.2746          |
| 0.548         | 68.0  | 68   | 0.2688          |
| 0.548         | 69.0  | 69   | 0.2643          |
| 0.548         | 70.0  | 70   | 0.2581          |
| 0.548         | 71.0  | 71   | 0.2523          |
| 0.548         | 72.0  | 72   | 0.2490          |
| 0.548         | 73.0  | 73   | 0.2468          |
| 0.548         | 74.0  | 74   | 0.2404          |
| 0.1741        | 75.0  | 75   | 0.2394          |
| 0.1741        | 76.0  | 76   | 0.2382          |
| 0.1741        | 77.0  | 77   | 0.2373          |
| 0.1741        | 78.0  | 78   | 0.2366          |
| 0.1741        | 79.0  | 79   | 0.2361          |
| 0.1741        | 80.0  | 80   | 0.2358          |
| 0.1741        | 81.0  | 81   | 0.2355          |
| 0.1741        | 82.0  | 82   | 0.2352          |
| 0.1741        | 83.0  | 83   | 0.2350          |
| 0.1741        | 84.0  | 84   | 0.2348          |
| 0.1741        | 85.0  | 85   | 0.2345          |
| 0.1741        | 86.0  | 86   | 0.2343          |
| 0.1741        | 87.0  | 87   | 0.2342          |
| 0.1741        | 88.0  | 88   | 0.2340          |
| 0.1741        | 89.0  | 89   | 0.2339          |
| 0.1741        | 90.0  | 90   | 0.2337          |
| 0.1741        | 91.0  | 91   | 0.2336          |
| 0.1741        | 92.0  | 92   | 0.2335          |
| 0.1741        | 93.0  | 93   | 0.2334          |
| 0.1741        | 94.0  | 94   | 0.2333          |
| 0.1741        | 95.0  | 95   | 0.2333          |
| 0.1741        | 96.0  | 96   | 0.2332          |
| 0.1741        | 97.0  | 97   | 0.2331          |
| 0.1741        | 98.0  | 98   | 0.2331          |
| 0.1741        | 99.0  | 99   | 0.2331          |
| 0.1174        | 100.0 | 100  | 0.2331          |


### Framework versions

- PEFT 0.8.1
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1