---
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-combined-adapter-test
  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-combined-adapter-test

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: 0.2293
- Wer: 0.3752

## 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: 8
- 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.4783        | 0.1374 | 100  | 0.6403          | 0.69   |
| 0.5413        | 0.2747 | 200  | 0.3260          | 0.4931 |
| 0.437         | 0.4121 | 300  | 0.3014          | 0.4678 |
| 0.4402        | 0.5495 | 400  | 0.2982          | 0.4818 |
| 0.4153        | 0.6868 | 500  | 0.2936          | 0.4702 |
| 0.4154        | 0.8242 | 600  | 0.2884          | 0.4493 |
| 0.3789        | 0.9615 | 700  | 0.2806          | 0.4521 |
| 0.3667        | 1.0989 | 800  | 0.2764          | 0.4352 |
| 0.3929        | 1.2363 | 900  | 0.2763          | 0.4654 |
| 0.3847        | 1.3736 | 1000 | 0.2705          | 0.4406 |
| 0.3833        | 1.5110 | 1100 | 0.2697          | 0.4246 |
| 0.3742        | 1.6484 | 1200 | 0.2668          | 0.4250 |
| 0.3694        | 1.7857 | 1300 | 0.2690          | 0.4189 |
| 0.3494        | 1.9231 | 1400 | 0.2635          | 0.416  |
| 0.3724        | 2.0604 | 1500 | 0.2626          | 0.4323 |
| 0.3723        | 2.1978 | 1600 | 0.2598          | 0.4247 |
| 0.3505        | 2.3352 | 1700 | 0.2583          | 0.412  |
| 0.3393        | 2.4725 | 1800 | 0.2563          | 0.4128 |
| 0.3352        | 2.6099 | 1900 | 0.2545          | 0.4156 |
| 0.3516        | 2.7473 | 2000 | 0.2551          | 0.4315 |
| 0.3489        | 2.8846 | 2100 | 0.2560          | 0.4270 |
| 0.3512        | 3.0220 | 2200 | 0.2536          | 0.4039 |
| 0.339         | 3.1593 | 2300 | 0.2490          | 0.3989 |
| 0.3374        | 3.2967 | 2400 | 0.2495          | 0.3964 |
| 0.3295        | 3.4341 | 2500 | 0.2518          | 0.4037 |
| 0.3391        | 3.5714 | 2600 | 0.2491          | 0.4077 |
| 0.3373        | 3.7088 | 2700 | 0.2445          | 0.3989 |
| 0.3097        | 3.8462 | 2800 | 0.2462          | 0.4118 |
| 0.3458        | 3.9835 | 2900 | 0.2443          | 0.4034 |
| 0.313         | 4.1209 | 3000 | 0.2433          | 0.3882 |
| 0.3171        | 4.2582 | 3100 | 0.2426          | 0.3968 |
| 0.3122        | 4.3956 | 3200 | 0.2430          | 0.3936 |
| 0.3255        | 4.5330 | 3300 | 0.2404          | 0.3822 |
| 0.3253        | 4.6703 | 3400 | 0.2356          | 0.3946 |
| 0.3341        | 4.8077 | 3500 | 0.2369          | 0.3872 |
| 0.3183        | 4.9451 | 3600 | 0.2345          | 0.3854 |
| 0.3461        | 5.0824 | 3700 | 0.2395          | 0.3828 |
| 0.3147        | 5.2198 | 3800 | 0.2359          | 0.3775 |
| 0.317         | 5.3571 | 3900 | 0.2320          | 0.3808 |
| 0.3094        | 5.4945 | 4000 | 0.2366          | 0.3797 |
| 0.2913        | 5.6319 | 4100 | 0.2357          | 0.3749 |
| 0.3195        | 5.7692 | 4200 | 0.2332          | 0.3694 |
| 0.3189        | 5.9066 | 4300 | 0.2313          | 0.3870 |
| 0.3105        | 6.0440 | 4400 | 0.2326          | 0.3806 |
| 0.2937        | 6.1813 | 4500 | 0.2346          | 0.3784 |
| 0.3088        | 6.3187 | 4600 | 0.2313          | 0.3726 |
| 0.2852        | 6.4560 | 4700 | 0.2307          | 0.3709 |
| 0.3083        | 6.5934 | 4800 | 0.2293          | 0.3752 |
| 0.3194        | 6.7308 | 4900 | 0.2292          | 0.3711 |
| 0.297         | 6.8681 | 5000 | 0.2303          | 0.3715 |
| 0.3086        | 7.0055 | 5100 | 0.2340          | 0.4027 |
| 0.3058        | 7.1429 | 5200 | 0.2294          | 0.3665 |


### Framework versions

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