---
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_da0.3
  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_da0.3

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: 5.8781
- Wer: 0.7877

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 24.822        | 17.86  | 250  | 8.9601          | 1.0    |
| 6.2153        | 35.71  | 500  | 5.9697          | 1.0    |
| 3.5607        | 53.57  | 750  | 5.5112          | 1.0    |
| 3.2305        | 71.43  | 1000 | 5.6378          | 1.0    |
| 2.9631        | 89.29  | 1250 | 5.4385          | 1.0    |
| 2.5463        | 107.14 | 1500 | 5.2806          | 0.9953 |
| 2.1207        | 125.0  | 1750 | 5.3065          | 0.9492 |
| 1.7629        | 142.86 | 2000 | 5.4365          | 0.9158 |
| 1.4631        | 160.71 | 2250 | 5.1678          | 0.8667 |
| 1.2158        | 178.57 | 2500 | 5.3097          | 0.8428 |
| 1.0507        | 196.43 | 2750 | 5.6917          | 0.8279 |
| 0.9326        | 214.29 | 3000 | 5.7407          | 0.8197 |
| 0.8245        | 232.14 | 3250 | 5.5588          | 0.8039 |
| 0.7415        | 250.0  | 3500 | 5.7107          | 0.7860 |
| 0.694         | 267.86 | 3750 | 5.8551          | 0.7971 |
| 0.6634        | 285.71 | 4000 | 5.8781          | 0.7877 |


### Framework versions

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