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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: fl_asr_speech_recognition |
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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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# fl_asr_speech_recognition |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2947 |
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- Wer: 0.1449 |
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- Cer: 0.0451 |
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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: 0.0001 |
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- train_batch_size: 4 |
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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: 500 |
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- num_epochs: 200 |
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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 | Cer | |
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|:-------------:|:--------:|:-----:|:---------------:|:------:|:------:| |
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| 0.625 | 12.6582 | 1000 | 0.4832 | 0.5625 | 0.1090 | |
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| 0.3037 | 25.3165 | 2000 | 0.3879 | 0.3665 | 0.0686 | |
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| 0.2127 | 37.9747 | 3000 | 0.4096 | 0.2926 | 0.0617 | |
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| 0.1767 | 50.6329 | 4000 | 0.3967 | 0.25 | 0.0552 | |
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| 0.1238 | 63.2911 | 5000 | 0.3024 | 0.2273 | 0.0529 | |
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| 0.0868 | 75.9494 | 6000 | 0.3768 | 0.2330 | 0.0487 | |
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| 0.0823 | 88.6076 | 7000 | 0.2742 | 0.2244 | 0.0420 | |
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| 0.0696 | 101.2658 | 8000 | 0.2792 | 0.2074 | 0.0383 | |
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| 0.0496 | 113.9241 | 9000 | 0.3362 | 0.1591 | 0.0359 | |
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| 0.0413 | 126.5823 | 10000 | 0.3061 | 0.1562 | 0.0400 | |
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| 0.0286 | 139.2405 | 11000 | 0.3264 | 0.1591 | 0.0406 | |
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| 0.0294 | 151.8987 | 12000 | 0.3046 | 0.1648 | 0.0424 | |
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| 0.0183 | 164.5570 | 13000 | 0.3083 | 0.1506 | 0.0400 | |
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| 0.0159 | 177.2152 | 14000 | 0.2947 | 0.1449 | 0.0451 | |
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| 0.009 | 189.8734 | 15000 | 0.3198 | 0.1477 | 0.0411 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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