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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- ./sample_speech.py
- generated_from_trainer
model-index:
- name: ko-xlsr
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. -->
# ko-xlsr
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4651
- Cer: 0.0828
## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.3673 | 3.17 | 1500 | 0.6104 | 0.1606 |
| 0.656 | 6.33 | 3000 | 0.4318 | 0.1129 |
| 0.4729 | 9.5 | 4500 | 0.4010 | 0.1028 |
| 0.3789 | 12.66 | 6000 | 0.3867 | 0.0977 |
| 0.3166 | 15.83 | 7500 | 0.3857 | 0.0936 |
| 0.267 | 18.99 | 9000 | 0.3891 | 0.0912 |
| 0.2286 | 22.16 | 10500 | 0.4074 | 0.0910 |
| 0.1967 | 25.32 | 12000 | 0.4079 | 0.0878 |
| 0.1712 | 28.49 | 13500 | 0.4289 | 0.0865 |
| 0.1493 | 31.65 | 15000 | 0.4456 | 0.0850 |
| 0.1333 | 34.82 | 16500 | 0.4573 | 0.0843 |
| 0.1191 | 37.98 | 18000 | 0.4633 | 0.0833 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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