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--- |
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base_model: nadsoft/Hamsa-tiny |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- nadsoft/QASR-Speech-Resource |
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metrics: |
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- wer |
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model-index: |
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- name: hamsa-tiny-pretrained |
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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: nadsoft/QASR-Speech-Resource default |
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type: nadsoft/QASR-Speech-Resource |
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metrics: |
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- name: Wer |
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type: wer |
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value: 28.726358005647974 |
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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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# hamsa-tiny-pretrained |
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This model is a fine-tuned version of [nadsoft/Hamsa-tiny](https://huggingface.co/nadsoft/Hamsa-tiny) on the nadsoft/QASR-Speech-Resource default dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3795 |
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- Wer: 28.7264 |
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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: 64 |
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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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- training_steps: 50000 |
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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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| 0.6597 | 0.1 | 2500 | 0.6394 | 48.8384 | |
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| 0.5442 | 0.2 | 5000 | 0.5455 | 41.8543 | |
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| 0.4954 | 0.3 | 7500 | 0.5018 | 39.8609 | |
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| 0.474 | 0.4 | 10000 | 0.4770 | 38.5534 | |
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| 0.4696 | 0.5 | 12500 | 0.4566 | 36.2515 | |
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| 0.4312 | 0.6 | 15000 | 0.4433 | 36.8780 | |
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| 0.4208 | 0.7 | 17500 | 0.4308 | 32.3714 | |
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| 0.4089 | 0.8 | 20000 | 0.4229 | 33.4109 | |
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| 0.4163 | 0.9 | 22500 | 0.4143 | 32.5423 | |
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| 0.3831 | 1.0 | 25000 | 0.4077 | 31.6951 | |
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| 0.3842 | 1.1 | 27500 | 0.4023 | 33.6316 | |
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| 0.3848 | 1.2 | 30000 | 0.3984 | 30.1099 | |
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| 0.3774 | 1.3 | 32500 | 0.3948 | 29.2864 | |
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| 0.3667 | 1.4 | 35000 | 0.3912 | 29.5166 | |
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| 0.3674 | 1.5 | 37500 | 0.3881 | 29.6115 | |
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| 0.3721 | 1.6 | 40000 | 0.3851 | 30.4065 | |
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| 0.3533 | 1.7 | 42500 | 0.3834 | 27.9693 | |
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| 0.3594 | 1.8 | 45000 | 0.3815 | 28.8569 | |
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| 0.3628 | 1.9 | 47500 | 0.3802 | 28.1260 | |
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| 0.3392 | 2.0 | 50000 | 0.3795 | 28.7264 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.0 |
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