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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: finetune_wav2vec2_base_six_500
  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. -->

# finetune_wav2vec2_base_six_500

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: 2.9216
- Wer: 100.0
- Cer: 99.5843

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- training_steps: 4500

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
| 4.1782        | 9.2593  | 500  | 2.9234          | 100.0   | 99.5862 |
| 2.0275        | 18.5185 | 1000 | 1.2454          | 57.1029 | 25.9689 |
| 0.565         | 27.7778 | 1500 | 1.1227          | 47.9586 | 22.3906 |
| 0.3036        | 37.0370 | 2000 | 1.2474          | 43.9597 | 21.5689 |
| 0.1954        | 46.2963 | 2500 | 1.3963          | 42.9251 | 20.9569 |
| 0.1336        | 55.5556 | 3000 | 1.5303          | 43.4843 | 21.5514 |
| 0.0999        | 64.8148 | 3500 | 1.4380          | 42.2260 | 20.7355 |
| 0.0797        | 74.0741 | 4000 | 1.5207          | 41.4430 | 20.6422 |
| 0.0648        | 83.3333 | 4500 | 1.5408          | 41.0235 | 20.4557 |


### Framework versions

- Transformers 4.40.2
- Pytorch 1.12.1+cu116
- Datasets 2.19.1
- Tokenizers 0.19.1