---
library_name: transformers
license: cc-by-nc-4.0
base_model: mms-meta/mms-zeroshot-300m
tags:
- automatic-speech-recognition
- genbed
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-zeroshot-300m-genbed-m-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-zeroshot-300m-genbed-m-model

This model is a fine-tuned version of [mms-meta/mms-zeroshot-300m](https://huggingface.co/mms-meta/mms-zeroshot-300m) on the GENBED - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3383
- Wer: 0.4761

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| No log        | 0.5510  | 200  | 2.3107          | 1.0    |
| No log        | 1.1019  | 400  | 0.4860          | 0.6380 |
| 2.8087        | 1.6529  | 600  | 0.4381          | 0.5988 |
| 2.8087        | 2.2039  | 800  | 0.4281          | 0.5855 |
| 0.6248        | 2.7548  | 1000 | 0.4056          | 0.5656 |
| 0.6248        | 3.3058  | 1200 | 0.4017          | 0.5513 |
| 0.6248        | 3.8567  | 1400 | 0.3904          | 0.5617 |
| 0.578         | 4.4077  | 1600 | 0.3776          | 0.5306 |
| 0.578         | 4.9587  | 1800 | 0.3722          | 0.5178 |
| 0.5343        | 5.5096  | 2000 | 0.3659          | 0.5152 |
| 0.5343        | 6.0606  | 2200 | 0.3614          | 0.5150 |
| 0.5343        | 6.6116  | 2400 | 0.3573          | 0.5016 |
| 0.5153        | 7.1625  | 2600 | 0.3625          | 0.5026 |
| 0.5153        | 7.7135  | 2800 | 0.3545          | 0.4867 |
| 0.4935        | 8.2645  | 3000 | 0.3506          | 0.4814 |
| 0.4935        | 8.8154  | 3200 | 0.3482          | 0.4922 |
| 0.4935        | 9.3664  | 3400 | 0.3383          | 0.4761 |
| 0.4731        | 9.9174  | 3600 | 0.3419          | 0.4645 |
| 0.4731        | 10.4683 | 3800 | 0.3391          | 0.4686 |
| 0.4619        | 11.0193 | 4000 | 0.3402          | 0.4576 |


### Framework versions

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