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--- |
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base_model: rinna/japanese-wav2vec2-base |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-kanji-base-unigram |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/tokudai-nishimura-lab/Emoto-ASR-training-log/runs/icxw1p2j) |
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# wav2vec2-kanji-base-unigram |
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This model is a fine-tuned version of [rinna/japanese-wav2vec2-base](https://huggingface.co/rinna/japanese-wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6841 |
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- Cer: 0.4426 |
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- Wer: 1.0 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: cosine |
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- lr_scheduler_warmup_steps: 77380 |
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- num_epochs: 20 |
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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 | Wer | |
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|:-------------:|:-----:|:------:|:---------------:|:------:|:-----:| |
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| 5.0463 | 1.0 | 19348 | 7.1017 | 0.9448 | 0.999 | |
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| 2.3465 | 2.0 | 38696 | 4.1177 | 0.6757 | 1.0 | |
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| 1.6622 | 3.0 | 58044 | 4.1171 | 0.6136 | 1.0 | |
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| 1.478 | 4.0 | 77392 | 2.8624 | 0.5836 | 1.0 | |
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| 1.3639 | 5.0 | 96740 | 3.2231 | 0.5709 | 1.0 | |
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| 1.2924 | 6.0 | 116088 | 3.6346 | 0.5807 | 1.0 | |
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| 1.2191 | 7.0 | 135436 | 2.4840 | 0.5444 | 1.0 | |
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| 1.1705 | 8.0 | 154784 | 2.5931 | 0.5403 | 1.0 | |
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| 1.117 | 9.0 | 174132 | 2.4750 | 0.5263 | 1.0 | |
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| 1.0689 | 10.0 | 193480 | 2.1332 | 0.5131 | 1.0 | |
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| 1.0371 | 11.0 | 212828 | 2.0070 | 0.4903 | 1.0 | |
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| 0.9922 | 12.0 | 232176 | 2.0196 | 0.4847 | 1.0 | |
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| 0.948 | 13.0 | 251524 | 1.7148 | 0.4597 | 1.0 | |
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| 0.9143 | 14.0 | 270872 | 1.5651 | 0.4506 | 1.0 | |
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| 0.8841 | 15.0 | 290220 | 1.7433 | 0.4530 | 1.0 | |
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| 0.8593 | 16.0 | 309568 | 1.7191 | 0.4528 | 1.0 | |
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| 0.8388 | 17.0 | 328916 | 1.6598 | 0.4455 | 1.0 | |
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| 0.8304 | 18.0 | 348264 | 1.6671 | 0.4434 | 1.0 | |
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| 0.8219 | 19.0 | 367612 | 1.6866 | 0.4426 | 1.0 | |
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| 0.8184 | 20.0 | 386960 | 1.6841 | 0.4426 | 1.0 | |
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### Framework versions |
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- Transformers 4.42.0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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