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

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the GENBED - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1823
- Wer: 0.3431

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.6556        | 0.1370 | 100  | 0.5951          | 0.6643 |
| 0.4415        | 0.2740 | 200  | 0.2734          | 0.4565 |
| 0.3448        | 0.4110 | 300  | 0.2482          | 0.4289 |
| 0.3459        | 0.5479 | 400  | 0.2392          | 0.4149 |
| 0.3184        | 0.6849 | 500  | 0.2304          | 0.4085 |
| 0.3058        | 0.8219 | 600  | 0.2372          | 0.4108 |
| 0.3077        | 0.9589 | 700  | 0.2271          | 0.4172 |
| 0.2812        | 1.0959 | 800  | 0.2217          | 0.3983 |
| 0.3297        | 1.2329 | 900  | 0.2209          | 0.3984 |
| 0.2817        | 1.3699 | 1000 | 0.2163          | 0.4124 |
| 0.2927        | 1.5068 | 1100 | 0.2146          | 0.3863 |
| 0.2806        | 1.6438 | 1200 | 0.2106          | 0.3851 |
| 0.2574        | 1.7808 | 1300 | 0.2098          | 0.3866 |
| 0.2829        | 1.9178 | 1400 | 0.2067          | 0.3772 |
| 0.2764        | 2.0548 | 1500 | 0.2076          | 0.3789 |
| 0.2635        | 2.1918 | 1600 | 0.2076          | 0.3769 |
| 0.2761        | 2.3288 | 1700 | 0.2068          | 0.3801 |
| 0.2854        | 2.4658 | 1800 | 0.1994          | 0.3645 |
| 0.2557        | 2.6027 | 1900 | 0.2016          | 0.3861 |
| 0.2717        | 2.7397 | 2000 | 0.2011          | 0.3734 |
| 0.2504        | 2.8767 | 2100 | 0.1989          | 0.3674 |
| 0.2606        | 3.0137 | 2200 | 0.1990          | 0.3835 |
| 0.2583        | 3.1507 | 2300 | 0.2028          | 0.3666 |
| 0.2591        | 3.2877 | 2400 | 0.1952          | 0.3507 |
| 0.2408        | 3.4247 | 2500 | 0.1988          | 0.3637 |
| 0.2485        | 3.5616 | 2600 | 0.1972          | 0.3593 |
| 0.2474        | 3.6986 | 2700 | 0.1949          | 0.3534 |
| 0.2398        | 3.8356 | 2800 | 0.1959          | 0.3697 |
| 0.2512        | 3.9726 | 2900 | 0.1906          | 0.3559 |
| 0.2266        | 4.1096 | 3000 | 0.1905          | 0.3482 |
| 0.2538        | 4.2466 | 3100 | 0.1916          | 0.3521 |
| 0.2268        | 4.3836 | 3200 | 0.1914          | 0.3895 |
| 0.2249        | 4.5205 | 3300 | 0.1897          | 0.3417 |
| 0.2416        | 4.6575 | 3400 | 0.1877          | 0.3458 |
| 0.2421        | 4.7945 | 3500 | 0.1872          | 0.3412 |
| 0.244         | 4.9315 | 3600 | 0.1855          | 0.3528 |
| 0.2371        | 5.0685 | 3700 | 0.1871          | 0.3447 |
| 0.2383        | 5.2055 | 3800 | 0.1833          | 0.3523 |
| 0.2409        | 5.3425 | 3900 | 0.1886          | 0.3487 |
| 0.2312        | 5.4795 | 4000 | 0.1848          | 0.3438 |
| 0.2261        | 5.6164 | 4100 | 0.1866          | 0.3469 |
| 0.2169        | 5.7534 | 4200 | 0.1841          | 0.3376 |
| 0.2283        | 5.8904 | 4300 | 0.1865          | 0.3412 |
| 0.2182        | 6.0274 | 4400 | 0.1823          | 0.3431 |
| 0.2141        | 6.1644 | 4500 | 0.1858          | 0.3403 |
| 0.2127        | 6.3014 | 4600 | 0.1876          | 0.3356 |
| 0.229         | 6.4384 | 4700 | 0.1863          | 0.3361 |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0