---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: checkpoints
  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. -->

# checkpoints

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:
- Loss: 0.2593
- Wer: 0.3195

## 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: 0.0004
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.9162        | 0.1621 | 100  | 0.5752          | 0.4898 |
| 0.4731        | 0.3241 | 200  | 0.3338          | 0.3774 |
| 0.4288        | 0.4862 | 300  | 0.3089          | 0.3573 |
| 0.3767        | 0.6483 | 400  | 0.3064          | 0.3607 |
| 0.4865        | 0.8104 | 500  | 0.3002          | 0.3558 |
| 0.3979        | 0.9724 | 600  | 0.2988          | 0.3565 |
| 0.3744        | 1.1345 | 700  | 0.2918          | 0.3596 |
| 0.4063        | 1.2966 | 800  | 0.2944          | 0.3497 |
| 0.3615        | 1.4587 | 900  | 0.2875          | 0.3543 |
| 0.3965        | 1.6207 | 1000 | 0.2790          | 0.3369 |
| 0.3846        | 1.7828 | 1100 | 0.2788          | 0.3372 |
| 0.3838        | 1.9449 | 1200 | 0.2747          | 0.3297 |
| 0.4338        | 2.1070 | 1300 | 0.2698          | 0.3361 |
| 0.2994        | 2.2690 | 1400 | 0.2688          | 0.3263 |
| 0.3604        | 2.4311 | 1500 | 0.2718          | 0.3259 |
| 0.3553        | 2.5932 | 1600 | 0.2687          | 0.3289 |
| 0.3616        | 2.7553 | 1700 | 0.2674          | 0.3232 |
| 0.3265        | 2.9173 | 1800 | 0.2656          | 0.3119 |
| 0.2892        | 3.0794 | 1900 | 0.2644          | 0.3221 |
| 0.2685        | 3.2415 | 2000 | 0.2646          | 0.3153 |
| 0.3268        | 3.4036 | 2100 | 0.2640          | 0.3183 |
| 0.2855        | 3.5656 | 2200 | 0.2620          | 0.3202 |
| 0.3351        | 3.7277 | 2300 | 0.2604          | 0.3195 |
| 0.4487        | 3.8898 | 2400 | 0.2593          | 0.3195 |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.6.0+cu126
- Datasets 3.2.0
- Tokenizers 0.21.0