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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- bemgen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-bemgen-balanced-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-bemgen-balanced-model
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BEMGEN - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2753
- Wer: 0.4201
## 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: 4
- seed: 42
- optimizer: Use 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: 30.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.8327 | 0.1031 | 100 | 0.8480 | 0.7889 |
| 0.5906 | 0.2062 | 200 | 0.3704 | 0.5819 |
| 0.4809 | 0.3093 | 300 | 0.3327 | 0.5039 |
| 0.4495 | 0.4124 | 400 | 0.3172 | 0.4894 |
| 0.4266 | 0.5155 | 500 | 0.3102 | 0.4632 |
| 0.4167 | 0.6186 | 600 | 0.3075 | 0.4716 |
| 0.4151 | 0.7216 | 700 | 0.2996 | 0.4829 |
| 0.3955 | 0.8247 | 800 | 0.2985 | 0.4712 |
| 0.3802 | 0.9278 | 900 | 0.2960 | 0.4926 |
| 0.392 | 1.0309 | 1000 | 0.2839 | 0.4374 |
| 0.375 | 1.1340 | 1100 | 0.2837 | 0.4318 |
| 0.3885 | 1.2371 | 1200 | 0.2812 | 0.4257 |
| 0.3824 | 1.3402 | 1300 | 0.2825 | 0.4255 |
| 0.3906 | 1.4433 | 1400 | 0.2794 | 0.4290 |
| 0.3465 | 1.5464 | 1500 | 0.2807 | 0.4283 |
| 0.3564 | 1.6495 | 1600 | 0.2773 | 0.4238 |
| 0.3617 | 1.7526 | 1700 | 0.2750 | 0.4452 |
| 0.3808 | 1.8557 | 1800 | 0.2783 | 0.4229 |
| 0.3661 | 1.9588 | 1900 | 0.2761 | 0.4517 |
| 0.3952 | 2.0619 | 2000 | 0.2753 | 0.4201 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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