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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2_common_voice_accents_indian
results: []
---
<!-- 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_common_voice_accents_indian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2692
## 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: 48
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 384
- total_eval_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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.5186 | 1.28 | 400 | 0.6937 |
| 0.3485 | 2.56 | 800 | 0.2323 |
| 0.2229 | 3.83 | 1200 | 0.2195 |
| 0.1877 | 5.11 | 1600 | 0.2147 |
| 0.1618 | 6.39 | 2000 | 0.2058 |
| 0.1434 | 7.67 | 2400 | 0.2077 |
| 0.132 | 8.95 | 2800 | 0.1995 |
| 0.1223 | 10.22 | 3200 | 0.2146 |
| 0.1153 | 11.5 | 3600 | 0.2117 |
| 0.1061 | 12.78 | 4000 | 0.2071 |
| 0.1003 | 14.06 | 4400 | 0.2219 |
| 0.0949 | 15.34 | 4800 | 0.2204 |
| 0.0889 | 16.61 | 5200 | 0.2162 |
| 0.0824 | 17.89 | 5600 | 0.2243 |
| 0.0784 | 19.17 | 6000 | 0.2323 |
| 0.0702 | 20.45 | 6400 | 0.2325 |
| 0.0665 | 21.73 | 6800 | 0.2334 |
| 0.0626 | 23.0 | 7200 | 0.2411 |
| 0.058 | 24.28 | 7600 | 0.2473 |
| 0.054 | 25.56 | 8000 | 0.2591 |
| 0.0506 | 26.84 | 8400 | 0.2577 |
| 0.0484 | 28.12 | 8800 | 0.2633 |
| 0.0453 | 29.39 | 9200 | 0.2692 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.4
- Tokenizers 0.11.6
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