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-demo-google-colab
  results: []
---

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# wav2vec2-base-timit-demo-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: 0.5436
- Wer: 0.3401

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5276        | 1.0   | 500   | 1.9983          | 1.0066 |
| 0.8606        | 2.01  | 1000  | 0.5323          | 0.5220 |
| 0.4339        | 3.01  | 1500  | 0.4697          | 0.4512 |
| 0.3026        | 4.02  | 2000  | 0.4342          | 0.4266 |
| 0.2297        | 5.02  | 2500  | 0.5001          | 0.4135 |
| 0.1939        | 6.02  | 3000  | 0.4350          | 0.3897 |
| 0.1613        | 7.03  | 3500  | 0.4740          | 0.3883 |
| 0.1452        | 8.03  | 4000  | 0.4289          | 0.3825 |
| 0.1362        | 9.04  | 4500  | 0.4721          | 0.3927 |
| 0.1146        | 10.04 | 5000  | 0.4707          | 0.3730 |
| 0.1061        | 11.04 | 5500  | 0.4470          | 0.3701 |
| 0.0947        | 12.05 | 6000  | 0.4694          | 0.3722 |
| 0.0852        | 13.05 | 6500  | 0.5222          | 0.3733 |
| 0.0741        | 14.06 | 7000  | 0.4881          | 0.3657 |
| 0.069         | 15.06 | 7500  | 0.4957          | 0.3677 |
| 0.0679        | 16.06 | 8000  | 0.5241          | 0.3634 |
| 0.0618        | 17.07 | 8500  | 0.5091          | 0.3564 |
| 0.0576        | 18.07 | 9000  | 0.5055          | 0.3557 |
| 0.0493        | 19.08 | 9500  | 0.5013          | 0.3515 |
| 0.0469        | 20.08 | 10000 | 0.5506          | 0.3530 |
| 0.044         | 21.08 | 10500 | 0.5564          | 0.3528 |
| 0.0368        | 22.09 | 11000 | 0.5213          | 0.3509 |
| 0.0355        | 23.09 | 11500 | 0.5707          | 0.3495 |
| 0.0357        | 24.1  | 12000 | 0.5558          | 0.3483 |
| 0.0285        | 25.1  | 12500 | 0.5613          | 0.3455 |
| 0.0285        | 26.1  | 13000 | 0.5533          | 0.3480 |
| 0.0266        | 27.11 | 13500 | 0.5526          | 0.3462 |
| 0.0249        | 28.11 | 14000 | 0.5488          | 0.3429 |
| 0.0237        | 29.12 | 14500 | 0.5436          | 0.3401 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu115
- Datasets 1.18.3
- Tokenizers 0.12.1
