---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr1e-4_at0.7_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_lr1e-4_at0.7_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: 6.2022
- Wer: 1.0580

## 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: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 18.007        | 4.46  | 250  | 4.3814          | 1.0    |
| 3.2628        | 8.93  | 500  | 3.8568          | 1.0    |
| 3.1079        | 13.39 | 750  | 3.9328          | 1.0    |
| 1.4764        | 17.86 | 1000 | 2.7696          | 1.0384 |
| 0.2321        | 22.32 | 1250 | 4.2808          | 1.0507 |
| 0.1312        | 26.79 | 1500 | 4.8707          | 1.0529 |
| 0.0793        | 31.25 | 1750 | 5.2587          | 1.0558 |
| 0.0546        | 35.71 | 2000 | 5.6739          | 1.0541 |
| 0.0401        | 40.18 | 2250 | 5.7379          | 1.0494 |
| 0.0303        | 44.64 | 2500 | 5.8382          | 1.0558 |
| 0.0255        | 49.11 | 2750 | 6.0859          | 1.0567 |
| 0.0223        | 53.57 | 3000 | 6.0789          | 1.0558 |
| 0.019         | 58.04 | 3250 | 6.2022          | 1.0580 |


### Framework versions

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