| --- |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-large-xlsr-53 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - common_voice_13_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Marathi_ASR_using_xlsr_wav2vec |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: common_voice_13_0 |
| type: common_voice_13_0 |
| config: mr |
| split: test |
| args: mr |
| metrics: |
| - name: Wer |
| type: wer |
| value: 0.7180765086206896 |
| --- |
| |
| <!-- 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. --> |
|
|
| # Marathi_ASR_using_xlsr_wav2vec |
|
|
| 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_13_0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7582 |
| - Wer: 0.7181 |
| |
| ## 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: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 300 |
| - num_epochs: 30 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-------:|:----:|:---------------:|:------:| |
| | No log | 2.6667 | 200 | 0.7381 | 0.7263 | |
| | 0.336 | 5.3333 | 400 | 0.7472 | 0.7289 | |
| | 0.336 | 8.0 | 600 | 0.7452 | 0.7215 | |
| | 0.3237 | 10.6667 | 800 | 0.7449 | 0.7212 | |
| | 0.3237 | 13.3333 | 1000 | 0.7546 | 0.7192 | |
| | 0.3104 | 16.0 | 1200 | 0.7565 | 0.7210 | |
| | 0.3104 | 18.6667 | 1400 | 0.7550 | 0.7193 | |
| | 0.3089 | 21.3333 | 1600 | 0.7551 | 0.7186 | |
| | 0.3089 | 24.0 | 1800 | 0.7572 | 0.7185 | |
| | 0.2993 | 26.6667 | 2000 | 0.7571 | 0.7175 | |
| | 0.2993 | 29.3333 | 2200 | 0.7582 | 0.7181 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.40.0 |
| - Pytorch 2.1.2 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
|
|
