---
library_name: transformers
language:
- bem
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- BIG_C/Bemba
metrics:
- wer
model-index:
- name: facebook/mms-1b-all
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: BIG_C
      type: BIG_C/Bemba
    metrics:
    - name: Wer
      type: wer
      value: 0.4635265611806601
---

<!-- 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. -->

# facebook/mms-1b-all

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BIG_C dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5796
- Model Preparation Time: 0.0177
- Wer: 0.4635
- Cer: 0.1168

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:------:|
| 5.2767        | 1.0   | 154  | 0.6576          | 0.0177                 | 0.5943 | 0.1359 |
| 0.7588        | 2.0   | 308  | 0.6085          | 0.0177                 | 0.5476 | 0.1268 |
| 0.7192        | 3.0   | 462  | 0.5971          | 0.0177                 | 0.5313 | 0.1248 |
| 0.7048        | 4.0   | 616  | 0.5944          | 0.0177                 | 0.5432 | 0.1246 |
| 0.6911        | 5.0   | 770  | 0.5889          | 0.0177                 | 0.5271 | 0.1226 |
| 0.679         | 6.0   | 924  | 0.5702          | 0.0177                 | 0.5111 | 0.1205 |
| 0.6623        | 7.0   | 1078 | 0.5724          | 0.0177                 | 0.5046 | 0.1201 |
| 0.65          | 8.0   | 1232 | 0.5605          | 0.0177                 | 0.5054 | 0.1209 |
| 0.6421        | 9.0   | 1386 | 0.5515          | 0.0177                 | 0.4993 | 0.1178 |
| 0.626         | 10.0  | 1540 | 0.5518          | 0.0177                 | 0.4914 | 0.1166 |
| 0.5999        | 11.0  | 1694 | 0.5358          | 0.0177                 | 0.4910 | 0.1161 |
| 0.5824        | 12.0  | 1848 | 0.5425          | 0.0177                 | 0.5016 | 0.1226 |
| 0.5723        | 13.0  | 2002 | 0.5325          | 0.0177                 | 0.5071 | 0.1195 |
| 0.5576        | 14.0  | 2156 | 0.5437          | 0.0177                 | 0.4880 | 0.1160 |
| 0.5498        | 15.0  | 2310 | 0.5725          | 0.0177                 | 0.5341 | 0.1466 |
| 0.5383        | 16.0  | 2464 | 0.5814          | 0.0177                 | 0.4721 | 0.1141 |
| 0.5283        | 17.0  | 2618 | 0.5483          | 0.0177                 | 0.4819 | 0.1170 |
| 0.5145        | 18.0  | 2772 | 0.5297          | 0.0177                 | 0.4931 | 0.1237 |
| 0.4977        | 19.0  | 2926 | 0.5283          | 0.0177                 | 0.4889 | 0.1208 |
| 0.4913        | 20.0  | 3080 | 0.5365          | 0.0177                 | 0.4776 | 0.1236 |
| 0.4822        | 21.0  | 3234 | 0.5562          | 0.0177                 | 0.4708 | 0.1149 |
| 0.4768        | 22.0  | 3388 | 0.5493          | 0.0177                 | 0.4804 | 0.1160 |
| 0.4598        | 23.0  | 3542 | 0.5574          | 0.0177                 | 0.4736 | 0.1165 |
| 0.4558        | 24.0  | 3696 | 0.5340          | 0.0177                 | 0.4766 | 0.1195 |
| 0.4516        | 25.0  | 3850 | 0.5703          | 0.0177                 | 0.4787 | 0.1143 |
| 0.44          | 26.0  | 4004 | 0.5329          | 0.0177                 | 0.4662 | 0.1144 |
| 0.4322        | 27.0  | 4158 | 0.5790          | 0.0177                 | 0.4738 | 0.1136 |
| 0.4264        | 28.0  | 4312 | 0.5581          | 0.0177                 | 0.4729 | 0.1133 |
| 0.4193        | 29.0  | 4466 | 0.5655          | 0.0177                 | 0.4642 | 0.1144 |
| 0.4115        | 30.0  | 4620 | 0.5521          | 0.0177                 | 0.4657 | 0.1173 |
| 0.4046        | 31.0  | 4774 | 0.5370          | 0.0177                 | 0.4626 | 0.1139 |
| 0.4037        | 32.0  | 4928 | 0.5517          | 0.0177                 | 0.4753 | 0.1173 |
| 0.4016        | 33.0  | 5082 | 0.5733          | 0.0177                 | 0.4566 | 0.1119 |
| 0.3928        | 34.0  | 5236 | 0.5542          | 0.0177                 | 0.4715 | 0.1164 |
| 0.3827        | 35.0  | 5390 | 0.5504          | 0.0177                 | 0.4587 | 0.1132 |
| 0.3828        | 36.0  | 5544 | 0.5541          | 0.0177                 | 0.4587 | 0.1126 |
| 0.3788        | 37.0  | 5698 | 0.5548          | 0.0177                 | 0.4551 | 0.1121 |
| 0.371         | 38.0  | 5852 | 0.5574          | 0.0177                 | 0.4543 | 0.1131 |
| 0.3712        | 39.0  | 6006 | 0.5709          | 0.0177                 | 0.4600 | 0.1114 |
| 0.3631        | 40.0  | 6160 | 0.5783          | 0.0177                 | 0.4655 | 0.1174 |
| 0.3561        | 41.0  | 6314 | 0.5753          | 0.0177                 | 0.4628 | 0.1151 |
| 0.3518        | 42.0  | 6468 | 0.5695          | 0.0177                 | 0.4691 | 0.1188 |
| 0.3472        | 43.0  | 6622 | 0.5802          | 0.0177                 | 0.4619 | 0.1119 |
| 0.3423        | 44.0  | 6776 | 0.5796          | 0.0177                 | 0.4636 | 0.1146 |
| 0.3352        | 45.0  | 6930 | 0.5940          | 0.0177                 | 0.4585 | 0.1145 |
| 0.3335        | 46.0  | 7084 | 0.5915          | 0.0177                 | 0.4679 | 0.1189 |
| 0.3294        | 47.0  | 7238 | 0.5885          | 0.0177                 | 0.4664 | 0.1165 |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1