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_5
  results: []
---

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# wav2vec2_common_voice_accents_5

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: 0.0027

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.4163        | 1.34  | 400  | 0.5520          |
| 0.3305        | 2.68  | 800  | 0.1698          |
| 0.2138        | 4.03  | 1200 | 0.1104          |
| 0.1714        | 5.37  | 1600 | 0.0944          |
| 0.1546        | 6.71  | 2000 | 0.0700          |
| 0.1434        | 8.05  | 2400 | 0.0610          |
| 0.1272        | 9.4   | 2800 | 0.0493          |
| 0.1183        | 10.74 | 3200 | 0.0371          |
| 0.1113        | 12.08 | 3600 | 0.0468          |
| 0.1013        | 13.42 | 4000 | 0.0336          |
| 0.0923        | 14.77 | 4400 | 0.0282          |
| 0.0854        | 16.11 | 4800 | 0.0410          |
| 0.0791        | 17.45 | 5200 | 0.0252          |
| 0.0713        | 18.79 | 5600 | 0.0128          |
| 0.0662        | 20.13 | 6000 | 0.0252          |
| 0.0635        | 21.48 | 6400 | 0.0080          |
| 0.0607        | 22.82 | 6800 | 0.0098          |
| 0.0557        | 24.16 | 7200 | 0.0069          |
| 0.0511        | 25.5  | 7600 | 0.0057          |
| 0.0474        | 26.85 | 8000 | 0.0046          |
| 0.045         | 28.19 | 8400 | 0.0037          |
| 0.0426        | 29.53 | 8800 | 0.0027          |


### Framework versions

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