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

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the TOIGEN - TOI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2197
- Wer: 0.3590

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 6.8474        | 0.4016  | 100  | 3.6385          | 0.9952 |
| 2.2373        | 0.8032  | 200  | 0.5181          | 0.6290 |
| 0.6093        | 1.2048  | 300  | 0.3649          | 0.5187 |
| 0.4813        | 1.6064  | 400  | 0.3151          | 0.4909 |
| 0.3843        | 2.0080  | 500  | 0.2994          | 0.4567 |
| 0.3805        | 2.4096  | 600  | 0.2818          | 0.4423 |
| 0.3591        | 2.8112  | 700  | 0.2811          | 0.4402 |
| 0.3164        | 3.2129  | 800  | 0.2688          | 0.4105 |
| 0.3351        | 3.6145  | 900  | 0.2569          | 0.4060 |
| 0.3442        | 4.0161  | 1000 | 0.2639          | 0.4    |
| 0.2996        | 4.4177  | 1100 | 0.2581          | 0.4085 |
| 0.3196        | 4.8193  | 1200 | 0.2444          | 0.3863 |
| 0.3147        | 5.2209  | 1300 | 0.2450          | 0.3863 |
| 0.2936        | 5.6225  | 1400 | 0.2414          | 0.3855 |
| 0.2894        | 6.0241  | 1500 | 0.2363          | 0.3722 |
| 0.2772        | 6.4257  | 1600 | 0.2452          | 0.3843 |
| 0.2565        | 6.8273  | 1700 | 0.2357          | 0.3759 |
| 0.3033        | 7.2289  | 1800 | 0.2358          | 0.3787 |
| 0.2651        | 7.6305  | 1900 | 0.2349          | 0.3634 |
| 0.2912        | 8.0321  | 2000 | 0.2305          | 0.3658 |
| 0.2554        | 8.4337  | 2100 | 0.2303          | 0.3678 |
| 0.2535        | 8.8353  | 2200 | 0.2269          | 0.3553 |
| 0.2368        | 9.2369  | 2300 | 0.2288          | 0.3610 |
| 0.2491        | 9.6386  | 2400 | 0.2244          | 0.3686 |
| 0.2678        | 10.0402 | 2500 | 0.2289          | 0.3561 |
| 0.2247        | 10.4418 | 2600 | 0.2234          | 0.3614 |
| 0.2773        | 10.8434 | 2700 | 0.2248          | 0.3541 |
| 0.2162        | 11.2450 | 2800 | 0.2197          | 0.3590 |
| 0.2526        | 11.6466 | 2900 | 0.2208          | 0.3521 |
| 0.2521        | 12.0482 | 3000 | 0.2230          | 0.3702 |
| 0.2218        | 12.4498 | 3100 | 0.2208          | 0.3529 |
| 0.2419        | 12.8514 | 3200 | 0.2204          | 0.3517 |


### Framework versions

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