---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-MGB3
  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. -->

# mms-MGB3

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9382
- Wer: 0.6591

## 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: 1e-05
- train_batch_size: 14
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.7535        | 0.13  | 250  | 8.6735          | 1.0023 |
| 3.2385        | 0.27  | 500  | 3.3341          | 1.0003 |
| 2.3512        | 0.4   | 750  | 2.0937          | 0.9027 |
| 1.4967        | 0.53  | 1000 | 1.3694          | 0.7637 |
| 1.3214        | 0.67  | 1250 | 1.2237          | 0.7347 |
| 1.2072        | 0.8   | 1500 | 1.1672          | 0.7176 |
| 1.1913        | 0.93  | 1750 | 1.1334          | 0.7108 |
| 1.1127        | 1.07  | 2000 | 1.1102          | 0.7044 |
| 1.1454        | 1.2   | 2250 | 1.0919          | 0.6996 |
| 1.1128        | 1.33  | 2500 | 1.0763          | 0.6955 |
| 1.086         | 1.47  | 2750 | 1.0629          | 0.6916 |
| 1.1285        | 1.6   | 3000 | 1.0503          | 0.6888 |
| 1.081         | 1.73  | 3250 | 1.0406          | 0.6886 |
| 1.0449        | 1.86  | 3500 | 1.0320          | 0.6857 |
| 1.0625        | 2.0   | 3750 | 1.0231          | 0.6849 |
| 1.0892        | 2.13  | 4000 | 1.0157          | 0.6824 |
| 1.0566        | 2.26  | 4250 | 1.0097          | 0.6795 |
| 1.0972        | 2.4   | 4500 | 1.0036          | 0.6747 |
| 1.0617        | 2.53  | 4750 | 0.9957          | 0.6744 |
| 1.0441        | 2.66  | 5000 | 0.9881          | 0.6756 |
| 1.0589        | 2.8   | 5250 | 0.9807          | 0.6718 |
| 1.0005        | 2.93  | 5500 | 0.9758          | 0.6713 |
| 1.0447        | 3.06  | 5750 | 0.9701          | 0.6694 |
| 0.9722        | 3.2   | 6000 | 0.9667          | 0.6664 |
| 0.9873        | 3.33  | 6250 | 0.9595          | 0.6675 |
| 0.9857        | 3.46  | 6500 | 0.9551          | 0.6633 |
| 0.9625        | 3.6   | 6750 | 0.9519          | 0.6633 |
| 0.9748        | 3.73  | 7000 | 0.9464          | 0.6607 |
| 0.9626        | 3.86  | 7250 | 0.9427          | 0.6617 |
| 1.0242        | 4.0   | 7500 | 0.9382          | 0.6591 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1
- Datasets 2.19.1
- Tokenizers 0.13.3