---
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-5hrs-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-5hrs-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: 0.2369
- Cer: 0.0801

## 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    |
|:-------------:|:-----:|:----:|:------:|:------:|
| 9.5784        | 1.0   | 183  | 0.9998 | 0.9646 |
| 1.9211        | 2.0   | 366  | 0.2887 | 0.0983 |
| 0.6977        | 3.0   | 549  | 0.2641 | 0.0915 |
| 0.6391        | 4.0   | 732  | 0.2568 | 0.0893 |
| 0.59          | 5.0   | 915  | 0.2502 | 0.0874 |
| 0.5654        | 6.0   | 1098 | 0.2489 | 0.0865 |
| 0.5544        | 7.0   | 1281 | 0.2459 | 0.0853 |
| 0.5385        | 8.0   | 1464 | 0.2443 | 0.0846 |
| 0.5256        | 9.0   | 1647 | 0.2442 | 0.0841 |
| 0.5152        | 10.0  | 1830 | 0.2420 | 0.0837 |
| 0.5116        | 11.0  | 2013 | 0.2411 | 0.0833 |
| 0.497         | 12.0  | 2196 | 0.2414 | 0.0829 |
| 0.4969        | 13.0  | 2379 | 0.2400 | 0.0826 |
| 0.4887        | 14.0  | 2562 | 0.2396 | 0.0824 |
| 0.4849        | 15.0  | 2745 | 0.2394 | 0.0820 |
| 0.473         | 16.0  | 2928 | 0.2396 | 0.0820 |
| 0.4732        | 17.0  | 3111 | 0.2403 | 0.0819 |
| 0.4648        | 18.0  | 3294 | 0.2396 | 0.0817 |
| 0.4608        | 19.0  | 3477 | 0.2397 | 0.0817 |
| 0.4583        | 20.0  | 3660 | 0.2397 | 0.0815 |
| 0.4579        | 21.0  | 3843 | 0.2402 | 0.0817 |
| 0.447         | 22.0  | 4026 | 0.2379 | 0.0813 |
| 0.4442        | 23.0  | 4209 | 0.2373 | 0.0809 |
| 0.439         | 24.0  | 4392 | 0.2373 | 0.0809 |
| 0.4381        | 25.0  | 4575 | 0.2376 | 0.0809 |
| 0.4386        | 26.0  | 4758 | 0.2377 | 0.0807 |
| 0.423         | 27.0  | 4941 | 0.2360 | 0.0804 |
| 0.428         | 28.0  | 5124 | 0.2366 | 0.0803 |
| 0.425         | 29.0  | 5307 | 0.2368 | 0.0804 |
| 0.4169        | 30.0  | 5490 | 0.2376 | 0.0803 |
| 0.4253        | 31.0  | 5673 | 0.2367 | 0.0802 |
| 0.4173        | 32.0  | 5856 | 0.2371 | 0.0802 |
| 0.414         | 33.0  | 6039 | 0.2362 | 0.0800 |
| 0.414         | 34.0  | 6222 | 0.2367 | 0.0803 |
| 0.4064        | 35.0  | 6405 | 0.2373 | 0.0801 |
| 0.402         | 36.0  | 6588 | 0.2370 | 0.0802 |
| 0.4035        | 37.0  | 6771 | 0.2369 | 0.0801 |


### Framework versions

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