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: wac2vec-lllfantomlll
  results: []
---

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# wac2vec-lllfantomlll

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: 0.5560
- Wer: 0.3417

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5768        | 1.0   | 500   | 2.0283          | 1.0238 |
| 0.9219        | 2.01  | 1000  | 0.5103          | 0.5022 |
| 0.4497        | 3.01  | 1500  | 0.4746          | 0.4669 |
| 0.3163        | 4.02  | 2000  | 0.4144          | 0.4229 |
| 0.2374        | 5.02  | 2500  | 0.4186          | 0.4161 |
| 0.2033        | 6.02  | 3000  | 0.4115          | 0.3975 |
| 0.1603        | 7.03  | 3500  | 0.4424          | 0.3817 |
| 0.1455        | 8.03  | 4000  | 0.4151          | 0.3918 |
| 0.1276        | 9.04  | 4500  | 0.4940          | 0.3798 |
| 0.108         | 10.04 | 5000  | 0.4580          | 0.3688 |
| 0.1053        | 11.04 | 5500  | 0.4243          | 0.3700 |
| 0.0929        | 12.05 | 6000  | 0.4999          | 0.3727 |
| 0.0896        | 13.05 | 6500  | 0.4991          | 0.3624 |
| 0.0748        | 14.06 | 7000  | 0.4924          | 0.3602 |
| 0.0681        | 15.06 | 7500  | 0.4908          | 0.3544 |
| 0.0619        | 16.06 | 8000  | 0.5021          | 0.3559 |
| 0.0569        | 17.07 | 8500  | 0.5448          | 0.3518 |
| 0.0549        | 18.07 | 9000  | 0.4919          | 0.3508 |
| 0.0478        | 19.08 | 9500  | 0.4704          | 0.3513 |
| 0.0437        | 20.08 | 10000 | 0.5058          | 0.3555 |
| 0.0421        | 21.08 | 10500 | 0.5127          | 0.3489 |
| 0.0362        | 22.09 | 11000 | 0.5439          | 0.3527 |
| 0.0322        | 23.09 | 11500 | 0.5418          | 0.3469 |
| 0.0327        | 24.1  | 12000 | 0.5298          | 0.3422 |
| 0.0292        | 25.1  | 12500 | 0.5511          | 0.3426 |
| 0.0246        | 26.1  | 13000 | 0.5349          | 0.3472 |
| 0.0251        | 27.11 | 13500 | 0.5646          | 0.3391 |
| 0.0214        | 28.11 | 14000 | 0.5821          | 0.3424 |
| 0.0217        | 29.12 | 14500 | 0.5560          | 0.3417 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
