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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-Bangla
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: bn
split: train+validation
args: bn
metrics:
- name: Wer
type: wer
value: 0.5442110214000156
---
<!-- 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. -->
# wav2vec2-large-xlsr-53-Bangla
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6125
- Wer: 0.5442
## 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: 0.0004
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.6881 | 2.28 | 600 | 1.0325 | 0.9634 |
| 0.8087 | 4.56 | 1200 | 0.6090 | 0.7430 |
| 0.5089 | 6.84 | 1800 | 0.5156 | 0.6615 |
| 0.3864 | 9.13 | 2400 | 0.5287 | 0.6676 |
| 0.3064 | 11.41 | 3000 | 0.5411 | 0.6278 |
| 0.2535 | 13.69 | 3600 | 0.5206 | 0.6149 |
| 0.216 | 15.97 | 4200 | 0.5596 | 0.6120 |
| 0.1852 | 18.25 | 4800 | 0.5658 | 0.5821 |
| 0.1653 | 20.53 | 5400 | 0.5938 | 0.5521 |
| 0.1499 | 22.81 | 6000 | 0.5825 | 0.5645 |
| 0.1323 | 25.09 | 6600 | 0.6151 | 0.5593 |
| 0.122 | 27.38 | 7200 | 0.6046 | 0.5556 |
| 0.1118 | 29.66 | 7800 | 0.6125 | 0.5442 |
### Framework versions
- Transformers 4.24.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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