---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-bemba-colab
  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. -->

# wav2vec2-large-mms-1b-bemba-colab

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1663
- Wer: 0.3303

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.6643        | 0.26  | 200  | 0.2147          | 0.3900 |
| 0.4271        | 0.52  | 400  | 0.1996          | 0.3634 |
| 0.4004        | 0.77  | 600  | 0.1911          | 0.3595 |
| 0.3789        | 1.03  | 800  | 0.1905          | 0.3544 |
| 0.3707        | 1.29  | 1000 | 0.1821          | 0.3461 |
| 0.3811        | 1.55  | 1200 | 0.1815          | 0.3586 |
| 0.3662        | 1.8   | 1400 | 0.1811          | 0.3433 |
| 0.3627        | 2.06  | 1600 | 0.1814          | 0.3443 |
| 0.3529        | 2.32  | 1800 | 0.1807          | 0.3375 |
| 0.3466        | 2.58  | 2000 | 0.1758          | 0.3299 |
| 0.3481        | 2.84  | 2200 | 0.1781          | 0.3408 |
| 0.3446        | 3.09  | 2400 | 0.1761          | 0.3316 |
| 0.3379        | 3.35  | 2600 | 0.1702          | 0.3305 |
| 0.3371        | 3.61  | 2800 | 0.1668          | 0.3258 |
| 0.3326        | 3.87  | 3000 | 0.1661          | 0.3212 |
| 0.3297        | 4.12  | 3200 | 0.1706          | 0.3358 |
| 0.3267        | 4.38  | 3400 | 0.1707          | 0.3322 |
| 0.3328        | 4.64  | 3600 | 0.1663          | 0.3303 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3