---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-all-sw-CV_Fleurs_AMMI_ALFFA-1hrs-v1
  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-all-sw-CV_Fleurs_AMMI_ALFFA-1hrs-v1

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
It achieves the following results on the evaluation set:
- Wer: 0.2505
- Cer: 0.0866

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Val Wer    | Val Cer    |
|:-------------:|:-----:|:----:|:------:|:------:|
| 16.1327       | 1.0   | 37   | 1.1533 | 2.6305 |
| 14.5509       | 2.0   | 74   | 1.4415 | 1.7715 |
| 11.4505       | 3.0   | 111  | 1.1493 | 0.8650 |
| 7.3358        | 4.0   | 148  | 1.0074 | 0.8544 |
| 4.2752        | 5.0   | 185  | 1.0009 | 0.8517 |
| 3.2479        | 6.0   | 222  | 1.0628 | 0.6094 |
| 2.322         | 7.0   | 259  | 0.7326 | 0.2337 |
| 1.5058        | 8.0   | 296  | 0.4135 | 0.1305 |
| 1.0304        | 9.0   | 333  | 0.3108 | 0.1034 |
| 0.8109        | 10.0  | 370  | 0.2843 | 0.0967 |
| 0.7432        | 11.0  | 407  | 0.2771 | 0.0948 |
| 0.6892        | 12.0  | 444  | 0.2725 | 0.0935 |
| 0.6813        | 13.0  | 481  | 0.2694 | 0.0928 |
| 0.6618        | 14.0  | 518  | 0.2683 | 0.0925 |
| 0.6347        | 15.0  | 555  | 0.2661 | 0.0917 |
| 0.6194        | 16.0  | 592  | 0.2648 | 0.0913 |
| 0.6234        | 17.0  | 629  | 0.2643 | 0.0909 |
| 0.6042        | 18.0  | 666  | 0.2610 | 0.0904 |
| 0.6092        | 19.0  | 703  | 0.2608 | 0.0900 |
| 0.6032        | 20.0  | 740  | 0.2588 | 0.0896 |
| 0.5886        | 21.0  | 777  | 0.2578 | 0.0892 |
| 0.5548        | 22.0  | 814  | 0.2559 | 0.0888 |
| 0.5701        | 23.0  | 851  | 0.2557 | 0.0887 |
| 0.591         | 24.0  | 888  | 0.2556 | 0.0885 |
| 0.5481        | 25.0  | 925  | 0.2545 | 0.0882 |
| 0.5437        | 26.0  | 962  | 0.2541 | 0.0879 |
| 0.537         | 27.0  | 999  | 0.2531 | 0.0877 |
| 0.555         | 28.0  | 1036 | 0.2526 | 0.0875 |
| 0.5391        | 29.0  | 1073 | 0.2518 | 0.0873 |
| 0.531         | 30.0  | 1110 | 0.2523 | 0.0873 |
| 0.5248        | 31.0  | 1147 | 0.2517 | 0.0872 |
| 0.5125        | 32.0  | 1184 | 0.2514 | 0.0871 |
| 0.5133        | 33.0  | 1221 | 0.2513 | 0.0870 |
| 0.4936        | 34.0  | 1258 | 0.2519 | 0.0870 |
| 0.5095        | 35.0  | 1295 | 0.2514 | 0.0868 |
| 0.5121        | 36.0  | 1332 | 0.2509 | 0.0867 |
| 0.4983        | 37.0  | 1369 | 0.2505 | 0.0866 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0