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: wav2vec2-7
  results: []
---

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# wav2vec2-7

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: 0.6017
- Wer: 0.5200

## 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: 32
- 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.1311        | 1.56  | 200  | 2.9839          | 1.0    |
| 2.5727        | 3.12  | 400  | 1.4962          | 1.0209 |
| 1.0187        | 4.69  | 600  | 0.7562          | 0.7859 |
| 0.637         | 6.25  | 800  | 0.6529          | 0.6960 |
| 0.4847        | 7.81  | 1000 | 0.6609          | 0.6745 |
| 0.3952        | 9.38  | 1200 | 0.5808          | 0.6220 |
| 0.3343        | 10.94 | 1400 | 0.5622          | 0.6004 |
| 0.2897        | 12.5  | 1600 | 0.8842          | 0.5980 |
| 0.2549        | 14.06 | 1800 | 0.6047          | 0.5765 |
| 0.2334        | 15.62 | 2000 | 0.6436          | 0.5699 |
| 0.2144        | 17.19 | 2200 | 0.5831          | 0.5593 |
| 0.1982        | 18.75 | 2400 | 0.6327          | 0.5620 |
| 0.1817        | 20.31 | 2600 | 0.8790          | 0.5456 |
| 0.1713        | 21.88 | 2800 | 0.9603          | 0.5362 |
| 0.163         | 23.44 | 3000 | 0.5940          | 0.5384 |
| 0.1539        | 25.0  | 3200 | 0.6058          | 0.5311 |
| 0.1392        | 26.56 | 3400 | 0.6131          | 0.5221 |
| 0.1386        | 28.12 | 3600 | 0.6066          | 0.5258 |
| 0.1351        | 29.69 | 3800 | 0.6017          | 0.5200 |


### Framework versions

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