---
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-male-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-male-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: 0.1298
- Wer: 0.1952

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.345         | 0.2463 | 100  | 0.4506          | 0.4026 |
| 0.353         | 0.4926 | 200  | 0.2066          | 0.2924 |
| 0.2989        | 0.7389 | 300  | 0.1829          | 0.2715 |
| 0.2402        | 0.9852 | 400  | 0.1674          | 0.2546 |
| 0.2302        | 1.2315 | 500  | 0.1582          | 0.2436 |
| 0.2279        | 1.4778 | 600  | 0.1602          | 0.2428 |
| 0.2264        | 1.7241 | 700  | 0.1507          | 0.2287 |
| 0.2276        | 1.9704 | 800  | 0.1496          | 0.2353 |
| 0.2088        | 2.2167 | 900  | 0.1460          | 0.2208 |
| 0.1881        | 2.4631 | 1000 | 0.1455          | 0.2165 |
| 0.2079        | 2.7094 | 1100 | 0.1418          | 0.2168 |
| 0.196         | 2.9557 | 1200 | 0.1404          | 0.2086 |
| 0.1782        | 3.2020 | 1300 | 0.1373          | 0.2078 |
| 0.1741        | 3.4483 | 1400 | 0.1343          | 0.1944 |
| 0.1948        | 3.6946 | 1500 | 0.1318          | 0.2137 |
| 0.1904        | 3.9409 | 1600 | 0.1307          | 0.2043 |
| 0.1762        | 4.1872 | 1700 | 0.1313          | 0.2003 |
| 0.1718        | 4.4335 | 1800 | 0.1275          | 0.1932 |
| 0.1595        | 4.6798 | 1900 | 0.1276          | 0.1952 |
| 0.1811        | 4.9261 | 2000 | 0.1290          | 0.1983 |
| 0.1477        | 5.1724 | 2100 | 0.1298          | 0.1952 |


### Framework versions

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