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: wav2vec2-2
  results: []
---

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# wav2vec2-2

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: 0.9253
- Wer: 0.8133

## 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: 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: 400
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.4469        | 0.34  | 200  | 3.7440          | 1.0    |
| 3.1152        | 0.69  | 400  | 3.3755          | 1.0    |
| 2.9228        | 1.03  | 600  | 3.0427          | 1.0    |
| 2.8661        | 1.38  | 800  | 2.9406          | 1.0    |
| 2.8402        | 1.72  | 1000 | 2.9034          | 1.0    |
| 2.8301        | 2.07  | 1200 | 2.8850          | 1.0    |
| 2.8088        | 2.41  | 1400 | 2.8479          | 1.0    |
| 2.6892        | 2.75  | 1600 | 2.5800          | 1.0    |
| 2.3249        | 3.1   | 1800 | 2.1310          | 1.0    |
| 1.9687        | 3.44  | 2000 | 1.7652          | 0.9982 |
| 1.7338        | 3.79  | 2200 | 1.5430          | 0.9974 |
| 1.5698        | 4.13  | 2400 | 1.3927          | 0.9985 |
| 1.4475        | 4.48  | 2600 | 1.3186          | 0.9911 |
| 1.3764        | 4.82  | 2800 | 1.2406          | 0.9647 |
| 1.3022        | 5.16  | 3000 | 1.1954          | 0.9358 |
| 1.2409        | 5.51  | 3200 | 1.1450          | 0.8990 |
| 1.1989        | 5.85  | 3400 | 1.1107          | 0.8794 |
| 1.1478        | 6.2   | 3600 | 1.0839          | 0.8667 |
| 1.106         | 6.54  | 3800 | 1.0507          | 0.8573 |
| 1.0792        | 6.88  | 4000 | 1.0179          | 0.8463 |
| 1.0636        | 7.23  | 4200 | 0.9974          | 0.8355 |
| 1.0224        | 7.57  | 4400 | 0.9757          | 0.8343 |
| 1.0166        | 7.92  | 4600 | 0.9641          | 0.8261 |
| 0.9925        | 8.26  | 4800 | 0.9553          | 0.8183 |
| 0.9934        | 8.61  | 5000 | 0.9466          | 0.8199 |
| 0.9741        | 8.95  | 5200 | 0.9353          | 0.8172 |
| 0.9613        | 9.29  | 5400 | 0.9331          | 0.8133 |
| 0.9714        | 9.64  | 5600 | 0.9272          | 0.8144 |
| 0.9593        | 9.98  | 5800 | 0.9253          | 0.8133 |


### Framework versions

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