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--- |
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language: |
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- zh |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- whucedar/datasets_stt_1 |
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metrics: |
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- wer |
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model-index: |
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- name: zh-CN-model-medium-1 - whucedar |
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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: datasets_stt_1 |
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type: whucedar/datasets_stt_1 |
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args: 'config: zh, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 188.47926267281105 |
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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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# zh-CN-model-medium-1 - whucedar |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the datasets_stt_1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1323 |
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- Wer: 188.4793 |
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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: 1e-05 |
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- train_batch_size: 16 |
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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: 50 |
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- training_steps: 500 |
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- mixed_precision_training: Native AMP |
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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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| 0.0241 | 1.5873 | 100 | 0.1363 | 158.9862 | |
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| 0.0042 | 3.1746 | 200 | 0.1312 | 239.6313 | |
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| 0.0043 | 4.7619 | 300 | 0.1316 | 215.2074 | |
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| 0.0013 | 6.3492 | 400 | 0.1312 | 203.6866 | |
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| 0.0006 | 7.9365 | 500 | 0.1323 | 188.4793 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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