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

This model is a fine-tuned version of [mms-meta/mms-zeroshot-300m](https://huggingface.co/mms-meta/mms-zeroshot-300m) on the BEMBASPEECH - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2038
- Wer: 0.4007

## 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        | 0.1405 | 200  | 2.2803          | 1.0    |
| No log        | 0.2811 | 400  | 0.2945          | 0.5101 |
| 2.741         | 0.4216 | 600  | 0.2641          | 0.4834 |
| 2.741         | 0.5622 | 800  | 0.2611          | 0.4743 |
| 0.5962        | 0.7027 | 1000 | 0.2608          | 0.4831 |
| 0.5962        | 0.8433 | 1200 | 0.2477          | 0.4563 |
| 0.5962        | 0.9838 | 1400 | 0.2407          | 0.4567 |
| 0.536         | 1.1244 | 1600 | 0.2343          | 0.4412 |
| 0.536         | 1.2649 | 1800 | 0.2307          | 0.4423 |
| 0.5221        | 1.4055 | 2000 | 0.2252          | 0.4348 |
| 0.5221        | 1.5460 | 2200 | 0.2228          | 0.4326 |
| 0.5221        | 1.6866 | 2400 | 0.2162          | 0.4253 |
| 0.5027        | 1.8271 | 2600 | 0.2200          | 0.4188 |
| 0.5027        | 1.9677 | 2800 | 0.2131          | 0.4142 |
| 0.4818        | 2.1082 | 3000 | 0.2281          | 0.4281 |
| 0.4818        | 2.2488 | 3200 | 0.2178          | 0.4147 |
| 0.4818        | 2.3893 | 3400 | 0.2123          | 0.4155 |
| 0.4619        | 2.5299 | 3600 | 0.2142          | 0.4079 |
| 0.4619        | 2.6704 | 3800 | 0.2156          | 0.4011 |
| 0.464         | 2.8110 | 4000 | 0.2072          | 0.4009 |
| 0.464         | 2.9515 | 4200 | 0.2128          | 0.4013 |
| 0.464         | 3.0921 | 4400 | 0.2056          | 0.3982 |
| 0.4464        | 3.2326 | 4600 | 0.2038          | 0.4007 |
| 0.4464        | 3.3732 | 4800 | 0.2089          | 0.3987 |
| 0.4418        | 3.5137 | 5000 | 0.2043          | 0.4009 |
| 0.4418        | 3.6543 | 5200 | 0.2050          | 0.3964 |


### Framework versions

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