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: wav2vec2-15
  results: []
---

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# wav2vec2-15

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: 0.8623
- Wer: 0.8585

## 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: 1e-05
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.6808        | 1.37  | 200  | 3.7154          | 1.0    |
| 3.0784        | 2.74  | 400  | 3.1542          | 1.0    |
| 2.8919        | 4.11  | 600  | 2.9918          | 1.0    |
| 2.8317        | 5.48  | 800  | 2.8971          | 1.0    |
| 2.7958        | 6.85  | 1000 | 2.8409          | 1.0    |
| 2.7699        | 8.22  | 1200 | 2.8278          | 1.0    |
| 2.6365        | 9.59  | 1400 | 2.4657          | 1.0    |
| 2.1096        | 10.96 | 1600 | 1.8358          | 0.9988 |
| 1.6485        | 12.33 | 1800 | 1.4525          | 0.9847 |
| 1.3967        | 13.7  | 2000 | 1.2467          | 0.9532 |
| 1.2492        | 15.07 | 2200 | 1.1261          | 0.9376 |
| 1.1543        | 16.44 | 2400 | 1.0654          | 0.9194 |
| 1.0863        | 17.81 | 2600 | 1.0136          | 0.9161 |
| 1.0275        | 19.18 | 2800 | 0.9601          | 0.8827 |
| 0.9854        | 20.55 | 3000 | 0.9435          | 0.8878 |
| 0.9528        | 21.92 | 3200 | 0.9170          | 0.8807 |
| 0.926         | 23.29 | 3400 | 0.9121          | 0.8783 |
| 0.9025        | 24.66 | 3600 | 0.8884          | 0.8646 |
| 0.8909        | 26.03 | 3800 | 0.8836          | 0.8690 |
| 0.8717        | 27.4  | 4000 | 0.8810          | 0.8646 |
| 0.8661        | 28.77 | 4200 | 0.8623          | 0.8585 |


### Framework versions

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