---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.8_da0.05
  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_at0.8_da0.05

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: 3.9827
- Wer: 1.0295

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 43.0808       | 83.33   | 250  | 28.8440         | 1.0    |
| 8.5391        | 166.67  | 500  | 3.7744          | 1.0    |
| 3.2564        | 250.0   | 750  | 3.1400          | 1.0    |
| 3.0586        | 333.33  | 1000 | 3.1144          | 1.0    |
| 2.9982        | 416.67  | 1250 | 3.0792          | 1.0    |
| 2.927         | 500.0   | 1500 | 3.0777          | 1.0    |
| 2.7925        | 583.33  | 1750 | 3.0732          | 1.0    |
| 2.577         | 666.67  | 2000 | 3.0084          | 1.0    |
| 2.2523        | 750.0   | 2250 | 2.9828          | 1.0    |
| 1.8719        | 833.33  | 2500 | 3.1056          | 1.0026 |
| 1.5177        | 916.67  | 2750 | 3.3320          | 1.0154 |
| 1.233         | 1000.0  | 3000 | 3.5057          | 1.0184 |
| 1.0527        | 1083.33 | 3250 | 3.7065          | 1.0325 |
| 0.9262        | 1166.67 | 3500 | 3.8646          | 1.0316 |
| 0.8456        | 1250.0  | 3750 | 3.9958          | 1.0295 |
| 0.8247        | 1333.33 | 4000 | 3.9827          | 1.0295 |


### Framework versions

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