---
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: 1.4372
- Wer: 0.1666

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 18.4042       | 4.03  | 250  | 4.2497          | 1.0    |
| 3.3741        | 8.06  | 500  | 3.2004          | 1.0    |
| 3.1004        | 12.1  | 750  | 3.1159          | 1.0    |
| 2.3298        | 16.13 | 1000 | 1.0486          | 0.7809 |
| 0.5044        | 20.16 | 1250 | 0.6083          | 0.3464 |
| 0.27          | 24.19 | 1500 | 0.6948          | 0.2456 |
| 0.1833        | 28.23 | 1750 | 0.9908          | 0.1956 |
| 0.1324        | 32.26 | 2000 | 1.0134          | 0.1995 |
| 0.1027        | 36.29 | 2250 | 1.3176          | 0.1760 |
| 0.0852        | 40.32 | 2500 | 1.1929          | 0.1837 |
| 0.0703        | 44.35 | 2750 | 1.3824          | 0.1670 |
| 0.0601        | 48.39 | 3000 | 1.3337          | 0.1674 |
| 0.0546        | 52.42 | 3250 | 1.3566          | 0.1717 |
| 0.05          | 56.45 | 3500 | 1.4653          | 0.1670 |
| 0.046         | 60.48 | 3750 | 1.4321          | 0.1696 |
| 0.0452        | 64.52 | 4000 | 1.4372          | 0.1666 |


### Framework versions

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