---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: bambara-mms-1-hour-jeli-asr-hf
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/gcpr6xh9)
# bambara-mms-1-hour-jeli-asr-hf

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: 3.3954
- Wer: 0.7301
- Cer: 0.3627

## 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: 16
- 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: 500
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 1.6441        | 8.0   | 500  | 1.6965          | 0.7606 | 0.3865 |
| 0.9143        | 16.0  | 1000 | 2.0093          | 0.7460 | 0.3704 |
| 0.5249        | 24.0  | 1500 | 2.2733          | 0.7912 | 0.3808 |
| 0.3111        | 32.0  | 2000 | 2.7380          | 0.7231 | 0.3678 |
| 0.1826        | 40.0  | 2500 | 3.0810          | 0.7323 | 0.3626 |
| 0.1135        | 48.0  | 3000 | 3.3954          | 0.7301 | 0.3627 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.1.0+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3