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README.md
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---
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license: cc-by-nc-4.0
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base_model: facebook/mms-1b-l1107
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_13_0
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metrics:
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- wer
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model-index:
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- name: wav2vec2-large-mms-1b-korean-colab
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: common_voice_13_0
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type: common_voice_13_0
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config: ko
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split: test
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args: ko
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metrics:
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- name: Wer
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type: wer
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value: 0.9929506545820745
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# wav2vec2-large-mms-1b-korean-colab
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This model is a fine-tuned version of [facebook/mms-1b-l1107](https://huggingface.co/facebook/mms-1b-l1107) on the common_voice_13_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 7.8135
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- Wer: 0.9930
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.001
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 10.9747 | 2.63 | 100 | 7.8812 | 0.9990 |
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| 5.9431 | 5.26 | 200 | 8.2212 | 0.9960 |
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| 5.7372 | 7.89 | 300 | 8.1054 | 0.9930 |
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| 5.2582 | 10.53 | 400 | 8.2347 | 0.9940 |
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| 3.8725 | 13.16 | 500 | 7.7536 | 0.9940 |
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| 3.4454 | 15.79 | 600 | 7.7220 | 0.9930 |
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| 2.5989 | 18.42 | 700 | 7.8135 | 0.9930 |
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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