---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-ehf-test
  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. -->

# wav2vec2-ehf-test

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: 0.0648
- Wer: 0.1661

## 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 5.3431        | 0.7812  | 250  | 3.0217          | 1.0    |
| 2.9086        | 1.5625  | 500  | 2.9322          | 1.0    |
| 2.0836        | 2.3438  | 750  | 0.6583          | 0.5862 |
| 0.5632        | 3.125   | 1000 | 0.2877          | 0.3624 |
| 0.3427        | 3.9062  | 1250 | 0.1959          | 0.2823 |
| 0.2548        | 4.6875  | 1500 | 0.1463          | 0.2464 |
| 0.217         | 5.4688  | 1750 | 0.1467          | 0.2340 |
| 0.1769        | 6.25    | 2000 | 0.1217          | 0.2162 |
| 0.1564        | 7.0312  | 2250 | 0.1100          | 0.2090 |
| 0.1351        | 7.8125  | 2500 | 0.1062          | 0.2074 |
| 0.12          | 8.5938  | 2750 | 0.1055          | 0.2022 |
| 0.1161        | 9.375   | 3000 | 0.1039          | 0.2011 |
| 0.1085        | 10.1562 | 3250 | 0.0988          | 0.1912 |
| 0.097         | 10.9375 | 3500 | 0.0931          | 0.1879 |
| 0.0895        | 11.7188 | 3750 | 0.0873          | 0.1869 |
| 0.0846        | 12.5    | 4000 | 0.0807          | 0.1846 |
| 0.0815        | 13.2812 | 4250 | 0.0826          | 0.1836 |
| 0.0787        | 14.0625 | 4500 | 0.0780          | 0.1798 |
| 0.0714        | 14.8438 | 4750 | 0.0732          | 0.1774 |
| 0.0702        | 15.625  | 5000 | 0.0745          | 0.1778 |
| 0.0637        | 16.4062 | 5250 | 0.0741          | 0.1764 |
| 0.0608        | 17.1875 | 5500 | 0.0788          | 0.1758 |
| 0.0575        | 17.9688 | 5750 | 0.0726          | 0.1727 |
| 0.0529        | 18.75   | 6000 | 0.0727          | 0.1726 |
| 0.0539        | 19.5312 | 6250 | 0.0704          | 0.1709 |
| 0.0533        | 20.3125 | 6500 | 0.0683          | 0.1702 |
| 0.0483        | 21.0938 | 6750 | 0.0643          | 0.1667 |
| 0.0461        | 21.875  | 7000 | 0.0650          | 0.1696 |
| 0.0442        | 22.6562 | 7250 | 0.0697          | 0.1687 |
| 0.042         | 23.4375 | 7500 | 0.0696          | 0.1687 |
| 0.0389        | 24.2188 | 7750 | 0.0689          | 0.1682 |
| 0.0402        | 25.0    | 8000 | 0.0702          | 0.1683 |
| 0.0365        | 25.7812 | 8250 | 0.0709          | 0.1669 |
| 0.0315        | 26.5625 | 8500 | 0.0695          | 0.1672 |
| 0.0349        | 27.3438 | 8750 | 0.0667          | 0.1662 |
| 0.0292        | 28.125  | 9000 | 0.0666          | 0.1669 |
| 0.0311        | 28.9062 | 9250 | 0.0652          | 0.1666 |
| 0.0322        | 29.6875 | 9500 | 0.0648          | 0.1661 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.1.2
- Datasets 3.0.1
- Tokenizers 0.20.0