---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-bambara-5-hours-mali-asr-dataset
  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/wvhv58b0)
# mms-bambara-5-hours-mali-asr-dataset

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: 3.4671
- Wer: 0.5549
- Cer: 0.2722

## 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    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 1.7442        | 1.7241  | 500   | 1.5016          | 0.8074 | 0.3917 |
| 1.2377        | 3.4483  | 1000  | 1.4359          | 0.7090 | 0.3303 |
| 1.0648        | 5.1724  | 1500  | 1.6144          | 0.6935 | 0.3324 |
| 0.9677        | 6.8966  | 2000  | 1.5016          | 0.6696 | 0.3195 |
| 0.8607        | 8.6207  | 2500  | 1.5432          | 0.6492 | 0.3165 |
| 0.7663        | 10.3448 | 3000  | 1.7123          | 0.6522 | 0.3164 |
| 0.6906        | 12.0690 | 3500  | 1.7516          | 0.6208 | 0.3015 |
| 0.6025        | 13.7931 | 4000  | 1.7237          | 0.6187 | 0.3121 |
| 0.5379        | 15.5172 | 4500  | 1.8363          | 0.6310 | 0.3129 |
| 0.4772        | 17.2414 | 5000  | 1.8713          | 0.5894 | 0.2843 |
| 0.4267        | 18.9655 | 5500  | 2.0141          | 0.5962 | 0.2915 |
| 0.3759        | 20.6897 | 6000  | 2.0988          | 0.5882 | 0.2848 |
| 0.3404        | 22.4138 | 6500  | 2.2643          | 0.5826 | 0.2869 |
| 0.3042        | 24.1379 | 7000  | 2.4384          | 0.5733 | 0.2812 |
| 0.2825        | 25.8621 | 7500  | 2.3103          | 0.5718 | 0.2844 |
| 0.2543        | 27.5862 | 8000  | 2.1798          | 0.5724 | 0.2880 |
| 0.23          | 29.3103 | 8500  | 2.5892          | 0.5714 | 0.2843 |
| 0.2147        | 31.0345 | 9000  | 2.6667          | 0.5722 | 0.2822 |
| 0.1914        | 32.7586 | 9500  | 2.7395          | 0.5748 | 0.2812 |
| 0.1794        | 34.4828 | 10000 | 2.8872          | 0.5802 | 0.2847 |
| 0.1675        | 36.2069 | 10500 | 2.7069          | 0.5690 | 0.2827 |
| 0.1493        | 37.9310 | 11000 | 2.8134          | 0.5705 | 0.2840 |
| 0.1386        | 39.6552 | 11500 | 3.0683          | 0.5615 | 0.2771 |
| 0.1237        | 41.3793 | 12000 | 3.2212          | 0.5567 | 0.2753 |
| 0.117         | 43.1034 | 12500 | 3.2128          | 0.5593 | 0.2703 |
| 0.1082        | 44.8276 | 13000 | 3.2066          | 0.5562 | 0.2732 |
| 0.0978        | 46.5517 | 13500 | 3.4042          | 0.5551 | 0.2720 |
| 0.0927        | 48.2759 | 14000 | 3.4410          | 0.5541 | 0.2723 |
| 0.0915        | 50.0    | 14500 | 3.4671          | 0.5549 | 0.2722 |


### Framework versions

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