pytorch tensorboard 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: model-1h
  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. -->

# model-1h

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: 1.8317
- Wer: 1.0

## 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: 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: 5
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 11.4106       | 1.24  | 10   | 7.1597          | 1.0    |
| 4.777         | 2.47  | 20   | 3.9782          | 1.0    |
| 3.6585        | 3.71  | 30   | 3.3961          | 1.0    |
| 3.3143        | 4.94  | 40   | 3.1481          | 1.0    |
| 3.3318        | 6.24  | 50   | 3.0596          | 1.0    |
| 3.1368        | 7.47  | 60   | 2.9751          | 1.0    |
| 3.1058        | 8.71  | 70   | 2.9510          | 1.0    |
| 3.0605        | 9.94  | 80   | 2.9479          | 1.0    |
| 3.2043        | 11.24 | 90   | 2.9270          | 1.0    |
| 3.0424        | 12.47 | 100  | 2.9349          | 1.0    |
| 3.0374        | 13.71 | 110  | 2.9316          | 1.0    |
| 3.0256        | 14.94 | 120  | 2.9165          | 1.0    |
| 3.1724        | 16.24 | 130  | 2.9076          | 1.0    |
| 3.0119        | 17.47 | 140  | 2.9034          | 1.0    |
| 2.9937        | 18.71 | 150  | 2.8812          | 1.0    |
| 2.9775        | 19.94 | 160  | 2.8674          | 1.0    |
| 3.0826        | 21.24 | 170  | 2.8147          | 1.0    |
| 2.8717        | 22.47 | 180  | 2.7212          | 1.0    |
| 2.7714        | 23.71 | 190  | 2.6149          | 0.9952 |
| 2.634         | 24.94 | 200  | 2.4611          | 0.9984 |
| 2.5637        | 26.24 | 210  | 2.2734          | 1.0    |
| 2.237         | 27.47 | 220  | 2.0705          | 1.0    |
| 2.0381        | 28.71 | 230  | 1.9216          | 1.0    |
| 1.8788        | 29.94 | 240  | 1.8317          | 1.0    |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.1+cu102
- Datasets 1.18.3
- Tokenizers 0.10.3
