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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-ksponspeech-dataset
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. -->
# wav2vec2-ksponspeech-dataset
This model is a fine-tuned version of [Wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- WER(Word Error Rate) for Third party test data :
## Model description
Korean Wav2vec with Ksponspeech dataset.
This model was trained by two dataset :
- Train1 : https://huggingface.co/datasets/Taeham/wav2vec2-ksponspeech-train1 (1 ~ 20000th data in Ksponspeech)
- Train2 : https://huggingface.co/datasets/Taeham/wav2vec2-ksponspeech-train2 (20100 ~ 40100th data in Ksponspeech)
- Validation : https://huggingface.co/datasets/Taeham/wav2vec2-ksponspeech-test (20000 ~ 20100th data in Ksponspeech)
- Third party test : https://huggingface.co/datasets/Taeham/wav2vec2-ksponspeech-test (60000 ~ 20100th data in Ksponspeech)
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1
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