pytorch tensorboard 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: wav2vec2-1
  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. -->

# wav2vec2-1

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5980
- Wer: 0.4949

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.2691        | 1.37  | 200  | 2.9045          | 1.0    |
| 1.6356        | 2.74  | 400  | 0.9277          | 0.8678 |
| 0.8062        | 4.11  | 600  | 0.8200          | 0.7776 |
| 0.5983        | 5.48  | 800  | 0.6829          | 0.7161 |
| 0.4863        | 6.85  | 1000 | 0.6205          | 0.6507 |
| 0.407         | 8.22  | 1200 | 0.6519          | 0.6763 |
| 0.3641        | 9.59  | 1400 | 0.5771          | 0.6088 |
| 0.3291        | 10.96 | 1600 | 0.6548          | 0.6202 |
| 0.2905        | 12.33 | 1800 | 0.6538          | 0.5828 |
| 0.2613        | 13.7  | 2000 | 0.6281          | 0.5864 |
| 0.2354        | 15.07 | 2200 | 0.5936          | 0.5630 |
| 0.2145        | 16.44 | 2400 | 0.5877          | 0.5699 |
| 0.2008        | 17.81 | 2600 | 0.5469          | 0.5488 |
| 0.1751        | 19.18 | 2800 | 0.6453          | 0.5584 |
| 0.169         | 20.55 | 3000 | 0.5871          | 0.5357 |
| 0.1521        | 21.92 | 3200 | 0.6063          | 0.5318 |
| 0.1426        | 23.29 | 3400 | 0.5609          | 0.5171 |
| 0.1287        | 24.66 | 3600 | 0.6056          | 0.5126 |
| 0.1236        | 26.03 | 3800 | 0.5994          | 0.5074 |
| 0.1138        | 27.4  | 4000 | 0.5980          | 0.4944 |
| 0.1083        | 28.77 | 4200 | 0.5980          | 0.4949 |


### Framework versions

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