---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec_cv
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec_cv

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1760
- Wer: 1.0

## 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: 0.003
- train_batch_size: 6
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 7.1467        | 4.29  | 30   | 4.2173          | 1.0 |
| 6.8918        | 8.57  | 60   | 4.2004          | 1.0 |
| 5.4913        | 12.86 | 90   | 4.2007          | 1.0 |
| 5.3906        | 17.14 | 120  | 4.1765          | 1.0 |
| 4.9212        | 21.43 | 150  | 4.1714          | 1.0 |
| 4.3916        | 25.71 | 180  | 4.1811          | 1.0 |
| 5.2255        | 30.0  | 210  | 4.1633          | 1.0 |
| 4.501         | 34.29 | 240  | 4.2050          | 1.0 |
| 4.4328        | 38.57 | 270  | 4.1572          | 1.0 |
| 4.2136        | 42.86 | 300  | 4.1698          | 1.0 |
| 4.3353        | 47.14 | 330  | 4.1721          | 1.0 |
| 4.1805        | 51.43 | 360  | 4.1804          | 1.0 |
| 4.1695        | 55.71 | 390  | 4.1801          | 1.0 |
| 4.2978        | 60.0  | 420  | 4.1760          | 1.0 |


### Framework versions

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