---
tags:
- generated_from_trainer
model-index:
- name: pseudolabeling-step1-F04
  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. -->

# pseudolabeling-step1-F04

This model is a fine-tuned version of [yongjian/wav2vec2-large-a](https://huggingface.co/yongjian/wav2vec2-large-a) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5392
- Wer: 0.8870

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 21.4261       | 1.71  | 500  | 3.2064          | 1.0    |
| 2.9275        | 3.42  | 1000 | 2.6461          | 1.2637 |
| 2.49          | 5.14  | 1500 | 2.0627          | 1.2527 |
| 1.8582        | 6.85  | 2000 | 1.6367          | 1.1978 |
| 1.5071        | 8.56  | 2500 | 1.2845          | 1.1743 |
| 1.2181        | 10.27 | 3000 | 1.1395          | 1.1586 |
| 1.0386        | 11.99 | 3500 | 1.0155          | 1.0926 |
| 0.9307        | 13.7  | 4000 | 0.8144          | 1.0628 |
| 0.8073        | 15.41 | 4500 | 0.7666          | 1.1146 |
| 0.7209        | 17.12 | 5000 | 0.7020          | 1.0911 |
| 0.6618        | 18.84 | 5500 | 0.6829          | 1.0612 |
| 0.6079        | 20.55 | 6000 | 0.6023          | 0.9937 |
| 0.5242        | 22.26 | 6500 | 0.6057          | 0.9827 |
| 0.4848        | 23.97 | 7000 | 0.5802          | 0.9435 |
| 0.4602        | 25.68 | 7500 | 0.5376          | 0.9027 |
| 0.446         | 27.4  | 8000 | 0.5351          | 0.8964 |
| 0.4245        | 29.11 | 8500 | 0.5392          | 0.8870 |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2