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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-korean-demo-with-LM
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-large-xlsr-korean-demo-with-LM
This model is a fine-tuned version of [facebook/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:
- Loss: 0.3015
- Wer: 0.2113
## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.7496 | 1.08 | 400 | 3.1801 | 1.0 |
| 1.4505 | 2.16 | 800 | 0.5090 | 0.5659 |
| 0.566 | 3.23 | 1200 | 0.3600 | 0.4039 |
| 0.4265 | 4.31 | 1600 | 0.3224 | 0.3639 |
| 0.3611 | 5.39 | 2000 | 0.3152 | 0.3575 |
| 0.3035 | 6.47 | 2400 | 0.2814 | 0.3054 |
| 0.2863 | 7.55 | 2800 | 0.2749 | 0.2923 |
| 0.247 | 8.63 | 3200 | 0.2787 | 0.2884 |
| 0.232 | 9.7 | 3600 | 0.2924 | 0.2788 |
| 0.2069 | 10.78 | 4000 | 0.2668 | 0.2694 |
| 0.1922 | 11.86 | 4400 | 0.2873 | 0.2667 |
| 0.1747 | 12.94 | 4800 | 0.2870 | 0.2589 |
| 0.1755 | 14.02 | 5200 | 0.2778 | 0.2543 |
| 0.1546 | 15.09 | 5600 | 0.3062 | 0.2621 |
| 0.1456 | 16.17 | 6000 | 0.3043 | 0.2479 |
| 0.1404 | 17.25 | 6400 | 0.2885 | 0.2443 |
| 0.1308 | 18.33 | 6800 | 0.3274 | 0.2417 |
| 0.125 | 19.41 | 7200 | 0.2922 | 0.2401 |
| 0.1148 | 20.49 | 7600 | 0.2899 | 0.2300 |
| 0.1129 | 21.56 | 8000 | 0.2963 | 0.2276 |
| 0.1086 | 22.64 | 8400 | 0.2903 | 0.2209 |
| 0.097 | 23.72 | 8800 | 0.3041 | 0.2220 |
| 0.099 | 24.8 | 9200 | 0.2870 | 0.2168 |
| 0.0905 | 25.88 | 9600 | 0.2992 | 0.2176 |
| 0.0929 | 26.95 | 10000 | 0.2934 | 0.2115 |
| 0.0827 | 28.03 | 10400 | 0.2945 | 0.2141 |
| 0.0818 | 29.11 | 10800 | 0.3015 | 0.2113 |
### Usage
### Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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