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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr1e-4_at0.8_da0.4
  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_at0.8_da0.4

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: 2.1115
- Wer: 0.1952

## 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
- training_steps: 3500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 21.2157       | 13.16  | 250  | 4.1634          | 1.0    |
| 3.2337        | 26.32  | 500  | 3.1231          | 1.0    |
| 3.0575        | 39.47  | 750  | 3.0466          | 1.0    |
| 2.0739        | 52.63  | 1000 | 1.0677          | 0.6284 |
| 0.1758        | 65.79  | 1250 | 1.3711          | 0.3170 |
| 0.0675        | 78.95  | 1500 | 1.6521          | 0.2268 |
| 0.0355        | 92.11  | 1750 | 1.7313          | 0.2332 |
| 0.0209        | 105.26 | 2000 | 1.9720          | 0.2114 |
| 0.0162        | 118.42 | 2250 | 1.7569          | 0.2085 |
| 0.0099        | 131.58 | 2500 | 2.1623          | 0.1944 |
| 0.0071        | 144.74 | 2750 | 2.2067          | 0.1922 |
| 0.0066        | 157.89 | 3000 | 2.1246          | 0.1944 |
| 0.0059        | 171.05 | 3250 | 2.1484          | 0.1922 |
| 0.0045        | 184.21 | 3500 | 2.1115          | 0.1952 |


### Framework versions

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