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-base-timit-google-colab
  results: []
---

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# wav2vec2-base-timit-google-colab

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: 0.5506
- Wer: 0.3355

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.4326        | 1.0   | 500   | 1.5832          | 1.0063 |
| 0.8235        | 2.01  | 1000  | 0.5310          | 0.5134 |
| 0.4224        | 3.01  | 1500  | 0.4488          | 0.4461 |
| 0.2978        | 4.02  | 2000  | 0.4243          | 0.4191 |
| 0.232         | 5.02  | 2500  | 0.4532          | 0.4149 |
| 0.1902        | 6.02  | 3000  | 0.4732          | 0.3912 |
| 0.1628        | 7.03  | 3500  | 0.4807          | 0.3868 |
| 0.1437        | 8.03  | 4000  | 0.5295          | 0.3670 |
| 0.1241        | 9.04  | 4500  | 0.4602          | 0.3810 |
| 0.1206        | 10.04 | 5000  | 0.4691          | 0.3783 |
| 0.0984        | 11.04 | 5500  | 0.4500          | 0.3710 |
| 0.0929        | 12.05 | 6000  | 0.5247          | 0.3550 |
| 0.0914        | 13.05 | 6500  | 0.5546          | 0.3821 |
| 0.0742        | 14.06 | 7000  | 0.4874          | 0.3646 |
| 0.0729        | 15.06 | 7500  | 0.5327          | 0.3934 |
| 0.0663        | 16.06 | 8000  | 0.5769          | 0.3661 |
| 0.0575        | 17.07 | 8500  | 0.5191          | 0.3524 |
| 0.0588        | 18.07 | 9000  | 0.5155          | 0.3360 |
| 0.0456        | 19.08 | 9500  | 0.5135          | 0.3539 |
| 0.0444        | 20.08 | 10000 | 0.5380          | 0.3603 |
| 0.0419        | 21.08 | 10500 | 0.5275          | 0.3467 |
| 0.0366        | 22.09 | 11000 | 0.5072          | 0.3487 |
| 0.0331        | 23.09 | 11500 | 0.5450          | 0.3437 |
| 0.0345        | 24.1  | 12000 | 0.5138          | 0.3431 |
| 0.029         | 25.1  | 12500 | 0.5067          | 0.3413 |
| 0.0274        | 26.1  | 13000 | 0.5421          | 0.3422 |
| 0.0243        | 27.11 | 13500 | 0.5456          | 0.3392 |
| 0.0226        | 28.11 | 14000 | 0.5665          | 0.3368 |
| 0.0216        | 29.12 | 14500 | 0.5506          | 0.3355 |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 1.13.3
- Tokenizers 0.12.1
