---
language:
- bn
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_9_0
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
metrics:
- wer
model-index:
- name: XLS-R-300M - Bengali
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      type: mozilla-foundation/common_voice_9_0
      name: Common Voice 9
      args: bn
    metrics:
    - type: wer
      value: 20.150
      name: Test WER
    - name: Test CER
      type: cer
      value: 4.813
---

<!-- 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. -->

# 

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - BN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2297
- Wer: 0.2850
- Cer: 0.0660

## 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: 7.5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 8692
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.675         | 2.3   | 400  | 3.5052          | 1.0    | 1.0    |
| 3.0446        | 4.6   | 800  | 2.2759          | 1.0052 | 0.5215 |
| 1.7276        | 6.9   | 1200 | 0.7083          | 0.6697 | 0.1969 |
| 1.5171        | 9.2   | 1600 | 0.5328          | 0.5733 | 0.1568 |
| 1.4176        | 11.49 | 2000 | 0.4571          | 0.5161 | 0.1381 |
| 1.343         | 13.79 | 2400 | 0.3910          | 0.4522 | 0.1160 |
| 1.2743        | 16.09 | 2800 | 0.3534          | 0.4137 | 0.1044 |
| 1.2396        | 18.39 | 3200 | 0.3278          | 0.3877 | 0.0959 |
| 1.2035        | 20.69 | 3600 | 0.3109          | 0.3741 | 0.0917 |
| 1.1745        | 22.99 | 4000 | 0.2972          | 0.3618 | 0.0882 |
| 1.1541        | 25.29 | 4400 | 0.2836          | 0.3427 | 0.0832 |
| 1.1372        | 27.59 | 4800 | 0.2759          | 0.3357 | 0.0812 |
| 1.1048        | 29.89 | 5200 | 0.2669          | 0.3284 | 0.0783 |
| 1.0966        | 32.18 | 5600 | 0.2678          | 0.3249 | 0.0775 |
| 1.0747        | 34.48 | 6000 | 0.2547          | 0.3134 | 0.0748 |
| 1.0593        | 36.78 | 6400 | 0.2491          | 0.3077 | 0.0728 |
| 1.0417        | 39.08 | 6800 | 0.2450          | 0.3012 | 0.0711 |
| 1.024         | 41.38 | 7200 | 0.2402          | 0.2956 | 0.0694 |
| 1.0106        | 43.68 | 7600 | 0.2351          | 0.2915 | 0.0681 |
| 1.0014        | 45.98 | 8000 | 0.2328          | 0.2896 | 0.0673 |
| 0.9999        | 48.28 | 8400 | 0.2318          | 0.2866 | 0.0667 |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.1.1.dev0
- Tokenizers 0.12.1