---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.4_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_at0.4_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: 1.4243
- Wer: 0.2593

## 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 17.3727       | 4.03  | 250  | 8.4434          | 1.0    |
| 4.5158        | 8.06  | 500  | 5.6577          | 1.0    |
| 3.3968        | 12.1  | 750  | 5.5711          | 1.0    |
| 3.4087        | 16.13 | 1000 | 4.7248          | 1.0    |
| 3.2781        | 20.16 | 1250 | 4.1466          | 1.0004 |
| 3.0895        | 24.19 | 1500 | 4.0231          | 1.0004 |
| 2.7559        | 28.23 | 1750 | 2.6579          | 0.9735 |
| 1.8327        | 32.26 | 2000 | 1.5957          | 0.8979 |
| 0.7991        | 36.29 | 2250 | 1.1338          | 0.5656 |
| 0.4226        | 40.32 | 2500 | 1.1239          | 0.4088 |
| 0.2746        | 44.35 | 2750 | 1.2772          | 0.3430 |
| 0.1934        | 48.39 | 3000 | 1.2697          | 0.3187 |
| 0.1437        | 52.42 | 3250 | 1.3526          | 0.3033 |
| 0.1151        | 56.45 | 3500 | 1.3560          | 0.2777 |
| 0.0975        | 60.48 | 3750 | 1.3470          | 0.2606 |
| 0.0885        | 64.52 | 4000 | 1.4243          | 0.2593 |


### Framework versions

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