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

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the NYAGEN - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2166
- Wer: 0.2541

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 7.8679        | 0.3058 | 100  | 0.9128          | 0.6897 |
| 0.627         | 0.6116 | 200  | 0.3265          | 0.4386 |
| 0.5004        | 0.9174 | 300  | 0.2951          | 0.4040 |
| 0.4611        | 1.2232 | 400  | 0.2758          | 0.3659 |
| 0.4455        | 1.5291 | 500  | 0.2667          | 0.3599 |
| 0.4142        | 1.8349 | 600  | 0.2601          | 0.3514 |
| 0.3706        | 2.1407 | 700  | 0.2521          | 0.3479 |
| 0.3867        | 2.4465 | 800  | 0.2461          | 0.3128 |
| 0.3537        | 2.7523 | 900  | 0.2449          | 0.3158 |
| 0.3821        | 3.0581 | 1000 | 0.2413          | 0.2932 |
| 0.3626        | 3.3639 | 1100 | 0.2360          | 0.3083 |
| 0.3312        | 3.6697 | 1200 | 0.2336          | 0.2997 |
| 0.3322        | 3.9755 | 1300 | 0.2285          | 0.2967 |
| 0.3654        | 4.2813 | 1400 | 0.2235          | 0.2852 |
| 0.3241        | 4.5872 | 1500 | 0.2198          | 0.2807 |
| 0.2908        | 4.8930 | 1600 | 0.2167          | 0.2767 |
| 0.3299        | 5.1988 | 1700 | 0.2170          | 0.2747 |
| 0.3128        | 5.5046 | 1800 | 0.2147          | 0.2687 |
| 0.3094        | 5.8104 | 1900 | 0.2140          | 0.2742 |
| 0.309         | 6.1162 | 2000 | 0.2158          | 0.2702 |
| 0.3075        | 6.4220 | 2100 | 0.2127          | 0.2652 |
| 0.2823        | 6.7278 | 2200 | 0.2155          | 0.2672 |
| 0.3062        | 7.0336 | 2300 | 0.2133          | 0.2556 |
| 0.3012        | 7.3394 | 2400 | 0.2166          | 0.2541 |


### Framework versions

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