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---
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
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