---
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-female-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-female-model

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the LOZGEN - LOZ dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6218
- Wer: 0.3955

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 6.7809        | 0.8696  | 100  | 3.1491          | 0.9759 |
| 2.6957        | 1.7391  | 200  | 2.0011          | 0.9278 |
| 1.1829        | 2.6087  | 300  | 0.8064          | 0.6421 |
| 0.8527        | 3.4783  | 400  | 0.7470          | 0.5333 |
| 0.8376        | 4.3478  | 500  | 0.6996          | 0.4923 |
| 0.7567        | 5.2174  | 600  | 0.6792          | 0.4686 |
| 0.7014        | 6.0870  | 700  | 0.6882          | 0.4555 |
| 0.7242        | 6.9565  | 800  | 0.6557          | 0.4578 |
| 0.6895        | 7.8261  | 900  | 0.6532          | 0.4409 |
| 0.6543        | 8.6957  | 1000 | 0.6477          | 0.4278 |
| 0.6386        | 9.5652  | 1100 | 0.6592          | 0.4219 |
| 0.6145        | 10.4348 | 1200 | 0.6435          | 0.4257 |
| 0.6513        | 11.3043 | 1300 | 0.6570          | 0.4147 |
| 0.5788        | 12.1739 | 1400 | 0.6259          | 0.4086 |
| 0.6061        | 13.0435 | 1500 | 0.6179          | 0.4006 |
| 0.5647        | 13.9130 | 1600 | 0.6186          | 0.4006 |
| 0.5715        | 14.7826 | 1700 | 0.6271          | 0.3985 |
| 0.5502        | 15.6522 | 1800 | 0.6218          | 0.3962 |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0