---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- lozgen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-lozgen-balanced-model
  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-1b-lozgen-balanced-model

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the LOZGEN - TOI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5419
- Wer: 0.3662

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 6.6518        | 0.8130  | 100  | 3.1671          | 0.9943 |
| 2.6718        | 1.6260  | 200  | 2.2609          | 0.9316 |
| 1.4567        | 2.4390  | 300  | 0.7404          | 0.7192 |
| 0.7044        | 3.2520  | 400  | 0.6402          | 0.5321 |
| 0.6221        | 4.0650  | 500  | 0.6065          | 0.5166 |
| 0.6016        | 4.8780  | 600  | 0.5948          | 0.4787 |
| 0.5686        | 5.6911  | 700  | 0.5806          | 0.4641 |
| 0.6054        | 6.5041  | 800  | 0.5716          | 0.4486 |
| 0.4871        | 7.3171  | 900  | 0.5732          | 0.4446 |
| 0.5275        | 8.1301  | 1000 | 0.5667          | 0.4350 |
| 0.5199        | 8.9431  | 1100 | 0.5688          | 0.4300 |
| 0.5031        | 9.7561  | 1200 | 0.5516          | 0.4443 |
| 0.4533        | 10.5691 | 1300 | 0.5577          | 0.4179 |
| 0.4738        | 11.3821 | 1400 | 0.5536          | 0.4057 |
| 0.4925        | 12.1951 | 1500 | 0.5503          | 0.3969 |
| 0.441         | 13.0081 | 1600 | 0.5403          | 0.4005 |
| 0.4177        | 13.8211 | 1700 | 0.5563          | 0.3914 |
| 0.4589        | 14.6341 | 1800 | 0.5394          | 0.3876 |
| 0.4131        | 15.4472 | 1900 | 0.5425          | 0.3957 |
| 0.393         | 16.2602 | 2000 | 0.5469          | 0.3907 |
| 0.4235        | 17.0732 | 2100 | 0.5357          | 0.3878 |
| 0.4113        | 17.8862 | 2200 | 0.5391          | 0.3802 |
| 0.3781        | 18.6992 | 2300 | 0.5324          | 0.3728 |
| 0.3706        | 19.5122 | 2400 | 0.5463          | 0.3826 |
| 0.3617        | 20.3252 | 2500 | 0.5391          | 0.3697 |
| 0.401         | 21.1382 | 2600 | 0.5417          | 0.3664 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0