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

This model is a fine-tuned version of [mms-meta/mms-zeroshot-300m](https://huggingface.co./mms-meta/mms-zeroshot-300m) on the NATBED - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5928
- Wer: 0.5278

## 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        | 0.2503 | 200  | 2.6612          | 1.0    |
| No log        | 0.5006 | 400  | 0.7787          | 0.6601 |
| 3.3034        | 0.7509 | 600  | 0.7196          | 0.6194 |
| 3.3034        | 1.0013 | 800  | 0.6961          | 0.5966 |
| 0.8261        | 1.2516 | 1000 | 0.6695          | 0.5762 |
| 0.8261        | 1.5019 | 1200 | 0.6314          | 0.5728 |
| 0.8261        | 1.7522 | 1400 | 0.6478          | 0.5575 |
| 0.7513        | 2.0025 | 1600 | 0.6374          | 0.5554 |
| 0.7513        | 2.2528 | 1800 | 0.6033          | 0.5484 |
| 0.7173        | 2.5031 | 2000 | 0.6270          | 0.5419 |
| 0.7173        | 2.7534 | 2200 | 0.6057          | 0.5433 |
| 0.7173        | 3.0038 | 2400 | 0.5928          | 0.5278 |
| 0.7092        | 3.2541 | 2600 | 0.5980          | 0.5321 |
| 0.7092        | 3.5044 | 2800 | 0.5976          | 0.5261 |
| 0.696         | 3.7547 | 3000 | 0.6369          | 0.5248 |


### Framework versions

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