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--- |
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base_model: nadsoft/hamsa_small |
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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-small-finetuned-qasr |
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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: 22.587152044424403 |
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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-small-finetuned-qasr |
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This model is a fine-tuned version of [nadsoft/hamsa_small](https://huggingface.co/nadsoft/hamsa_small) 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: 0.2831 |
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- Wer: 22.5872 |
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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: 16 |
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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: 20000 |
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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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| 0.3207 | 0.03 | 2500 | 0.3458 | 24.4928 | |
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| 0.3264 | 0.05 | 5000 | 0.3316 | 23.4082 | |
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| 0.3223 | 0.08 | 7500 | 0.3239 | 25.1050 | |
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| 0.3121 | 0.1 | 10000 | 0.3143 | 23.4557 | |
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| 0.3103 | 0.13 | 12500 | 0.3079 | 23.4296 | |
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| 0.3041 | 0.15 | 15000 | 0.3033 | 23.2113 | |
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| 0.3077 | 0.18 | 17500 | 0.2998 | 21.7091 | |
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| 0.2867 | 0.2 | 20000 | 0.2943 | 20.1761 | |
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| 0.265 | 0.23 | 22500 | 0.2921 | 21.6522 | |
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| 0.3096 | 0.25 | 25000 | 0.2894 | 22.1505 | |
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| 0.2813 | 0.28 | 27500 | 0.2863 | 22.4993 | |
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| 0.2805 | 0.3 | 30000 | 0.2832 | 21.0114 | |
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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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