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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: 0.5172
- Cer: 0.1076
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.742 | 2.6 | 1500 | 0.9038 | 0.2330 |
| 0.9228 | 5.2 | 3000 | 0.6193 | 0.1656 |
| 0.6805 | 7.8 | 4500 | 0.5522 | 0.1481 |
| 0.5577 | 10.4 | 6000 | 0.5136 | 0.1349 |
| 0.4797 | 13.0 | 7500 | 0.5074 | 0.1312 |
| 0.4161 | 15.6 | 9000 | 0.4959 | 0.1243 |
| 0.3701 | 18.21 | 10500 | 0.4948 | 0.1224 |
| 0.3307 | 20.81 | 12000 | 0.4881 | 0.1199 |
| 0.2946 | 23.41 | 13500 | 0.4970 | 0.1179 |
| 0.2636 | 26.01 | 15000 | 0.4950 | 0.1145 |
| 0.2367 | 28.61 | 16500 | 0.4905 | 0.1119 |
| 0.2157 | 31.21 | 18000 | 0.5066 | 0.1110 |
| 0.1979 | 33.81 | 19500 | 0.5133 | 0.1103 |
| 0.1808 | 36.41 | 21000 | 0.5160 | 0.1091 |
| 0.17 | 39.01 | 22500 | 0.5129 | 0.1074 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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