---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.3_da1
  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. -->

# w2v2-base-pretrained_lr5e-5_at0.3_da1

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: 1.4352
- Wer: 0.1704

## 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: 5e-05
- 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
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 19.6725       | 3.97  | 250  | 4.9409          | 1.0    |
| 3.5043        | 7.94  | 500  | 3.2414          | 1.0    |
| 3.1162        | 11.9  | 750  | 3.1351          | 1.0    |
| 2.2138        | 15.87 | 1000 | 0.9146          | 0.9184 |
| 0.5308        | 19.84 | 1250 | 0.6292          | 0.4357 |
| 0.2762        | 23.81 | 1500 | 0.8713          | 0.2384 |
| 0.1894        | 27.78 | 1750 | 0.9537          | 0.1905 |
| 0.1339        | 31.75 | 2000 | 1.2355          | 0.1824 |
| 0.1002        | 35.71 | 2250 | 1.2193          | 0.1739 |
| 0.0858        | 39.68 | 2500 | 1.1557          | 0.1709 |
| 0.0711        | 43.65 | 2750 | 1.3591          | 0.1692 |
| 0.0589        | 47.62 | 3000 | 1.3372          | 0.1683 |
| 0.0525        | 51.59 | 3250 | 1.4133          | 0.1683 |
| 0.0464        | 55.56 | 3500 | 1.4969          | 0.1679 |
| 0.0436        | 59.52 | 3750 | 1.4262          | 0.1674 |
| 0.0401        | 63.49 | 4000 | 1.4352          | 0.1704 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1