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: wav2vec2-base_toy_train_data_masked_audio_10ms
  results: []
---

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# wav2vec2-base_toy_train_data_masked_audio_10ms

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: 1.2477
- Wer: 0.7145

## 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: 0.0001
- 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: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.1337        | 1.05  | 250  | 3.4081          | 0.9982 |
| 3.0792        | 2.1   | 500  | 3.2446          | 0.9982 |
| 2.0577        | 3.15  | 750  | 1.5839          | 0.9492 |
| 1.3639        | 4.2   | 1000 | 1.3279          | 0.8798 |
| 1.0814        | 5.25  | 1250 | 1.1629          | 0.8294 |
| 0.8722        | 6.3   | 1500 | 1.1305          | 0.8140 |
| 0.7602        | 7.35  | 1750 | 1.1241          | 0.7972 |
| 0.6982        | 8.4   | 2000 | 1.1429          | 0.7780 |
| 0.6494        | 9.45  | 2250 | 1.1047          | 0.7620 |
| 0.5924        | 10.5  | 2500 | 1.1756          | 0.7649 |
| 0.5385        | 11.55 | 2750 | 1.2230          | 0.7736 |
| 0.5026        | 12.6  | 3000 | 1.1783          | 0.7472 |
| 0.4973        | 13.65 | 3250 | 1.1613          | 0.7287 |
| 0.4726        | 14.7  | 3500 | 1.1923          | 0.7345 |
| 0.4521        | 15.75 | 3750 | 1.2153          | 0.7171 |
| 0.4552        | 16.81 | 4000 | 1.2485          | 0.7226 |
| 0.422         | 17.86 | 4250 | 1.2664          | 0.7240 |
| 0.3708        | 18.91 | 4500 | 1.2352          | 0.7148 |
| 0.3516        | 19.96 | 4750 | 1.2477          | 0.7145 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu102
- Datasets 2.0.0
- Tokenizers 0.11.6
