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--- |
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license: apache-2.0 |
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base_model: ctl/wav2vec2-large-xlsr-cantonese |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-zhhk |
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results: [] |
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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-xls-r-300m-zhhk |
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This model is a fine-tuned version of [ctl/wav2vec2-large-xlsr-cantonese](https://huggingface.co/ctl/wav2vec2-large-xlsr-cantonese) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.6213 |
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- Cer: 0.7864 |
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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: 0.0003 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 30 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.3317 | 1.35 | 400 | 4.5373 | 0.7915 | |
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| 0.3303 | 2.71 | 800 | 4.5198 | 0.7915 | |
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| 0.3288 | 4.06 | 1200 | 4.8663 | 0.8504 | |
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| 0.2901 | 5.41 | 1600 | 4.6080 | 0.8198 | |
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| 0.2819 | 6.77 | 2000 | 4.4941 | 0.7316 | |
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| 0.2629 | 8.12 | 2400 | 4.6927 | 0.8021 | |
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| 0.2363 | 9.48 | 2800 | 4.8796 | 0.8701 | |
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| 0.2205 | 10.83 | 3200 | 4.6338 | 0.8087 | |
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| 0.2171 | 12.18 | 3600 | 4.5740 | 0.7562 | |
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| 0.1875 | 13.54 | 4000 | 4.6072 | 0.7992 | |
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| 0.1824 | 14.89 | 4400 | 4.6546 | 0.7669 | |
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| 0.178 | 16.24 | 4800 | 4.6410 | 0.7961 | |
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| 0.1644 | 17.6 | 5200 | 4.7306 | 0.8236 | |
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| 0.155 | 18.95 | 5600 | 4.6632 | 0.7900 | |
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| 0.1396 | 20.3 | 6000 | 4.6239 | 0.8015 | |
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| 0.1411 | 21.66 | 6400 | 4.6007 | 0.7793 | |
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| 0.13 | 23.01 | 6800 | 4.5354 | 0.7475 | |
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| 0.1232 | 24.37 | 7200 | 4.6229 | 0.7600 | |
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| 0.1239 | 25.72 | 7600 | 4.6382 | 0.7727 | |
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| 0.1322 | 27.07 | 8000 | 4.6734 | 0.7902 | |
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| 0.1338 | 28.43 | 8400 | 4.6536 | 0.7861 | |
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| 0.1353 | 29.78 | 8800 | 4.6213 | 0.7864 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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