pytorch wav2vec2 automatic-speech-recognition transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: xlsr-wav2vec2-1
  results: []
---

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# xlsr-wav2vec2-1

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5437
- Wer: 0.4412

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.517         | 1.38  | 400  | 3.0431          | 1.0    |
| 1.8387        | 2.76  | 800  | 0.6552          | 0.7263 |
| 0.5971        | 4.14  | 1200 | 0.5308          | 0.5885 |
| 0.4153        | 5.52  | 1600 | 0.4667          | 0.5551 |
| 0.3388        | 6.9   | 2000 | 0.4428          | 0.5260 |
| 0.2803        | 8.28  | 2400 | 0.4915          | 0.5164 |
| 0.2613        | 9.65  | 2800 | 0.4904          | 0.4988 |
| 0.237         | 11.03 | 3200 | 0.4998          | 0.5075 |
| 0.2175        | 12.41 | 3600 | 0.4905          | 0.4983 |
| 0.1969        | 13.79 | 4000 | 0.4818          | 0.4877 |
| 0.1932        | 15.17 | 4400 | 0.5578          | 0.5006 |
| 0.1782        | 16.55 | 4800 | 0.4981          | 0.4949 |
| 0.1655        | 17.93 | 5200 | 0.4978          | 0.4940 |
| 0.1505        | 19.31 | 5600 | 0.5360          | 0.4896 |
| 0.1362        | 20.69 | 6000 | 0.5441          | 0.4709 |
| 0.1246        | 22.07 | 6400 | 0.5358          | 0.4650 |
| 0.1117        | 23.45 | 6800 | 0.5513          | 0.4716 |
| 0.107         | 24.83 | 7200 | 0.5344          | 0.4578 |
| 0.0963        | 26.21 | 7600 | 0.5073          | 0.4452 |
| 0.0846        | 27.59 | 8000 | 0.5335          | 0.4497 |
| 0.0799        | 28.96 | 8400 | 0.5437          | 0.4412 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
