pytorch wav2vec2 automatic-speech-recognition dataset:common_voice transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2_common_voice_accents_indian_only_rerun
  results: []
---

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# wav2vec2_common_voice_accents_indian_only_rerun

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: 1.2807

## 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: 588
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.6205        | 25.0  | 400  | 1.4584          |
| 0.3427        | 50.0  | 800  | 1.8377          |
| 0.1213        | 75.0  | 1200 | 1.6086          |
| 0.0643        | 100.0 | 1600 | 1.5136          |
| 0.0433        | 125.0 | 2000 | 1.4882          |
| 0.0323        | 150.0 | 2400 | 1.2204          |
| 0.0265        | 175.0 | 2800 | 1.3034          |
| 0.0206        | 200.0 | 3200 | 1.2866          |
| 0.0191        | 225.0 | 3600 | 1.2337          |
| 0.0148        | 250.0 | 4000 | 1.1729          |
| 0.0121        | 275.0 | 4400 | 1.2059          |
| 0.0105        | 300.0 | 4800 | 1.1246          |
| 0.01          | 325.0 | 5200 | 1.1397          |
| 0.0098        | 350.0 | 5600 | 1.1684          |
| 0.0073        | 375.0 | 6000 | 1.1030          |
| 0.0061        | 400.0 | 6400 | 1.2077          |
| 0.0049        | 425.0 | 6800 | 1.2653          |
| 0.0044        | 450.0 | 7200 | 1.1587          |
| 0.0037        | 475.0 | 7600 | 1.2283          |
| 0.0033        | 500.0 | 8000 | 1.1897          |
| 0.0026        | 525.0 | 8400 | 1.2633          |
| 0.0023        | 550.0 | 8800 | 1.2571          |
| 0.002         | 575.0 | 9200 | 1.2807          |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.4
- Tokenizers 0.11.6
