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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ami |
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metrics: |
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- wer |
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model-index: |
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- name: model_optimization |
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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: ami |
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type: ami |
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config: ihm |
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split: None |
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args: ihm |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.24598930481283424 |
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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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# model_optimization |
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This model was trained from scratch on the ami dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0220 |
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- Wer: 0.2460 |
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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: 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: 500 |
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- training_steps: 1000 |
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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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| 1.2804 | 50.0 | 250 | 1.8094 | 0.3636 | |
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| 0.637 | 100.0 | 500 | 2.6436 | 0.3155 | |
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| 0.4223 | 150.0 | 750 | 1.6623 | 0.2406 | |
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| 0.3273 | 200.0 | 1000 | 2.0220 | 0.2460 | |
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### Framework versions |
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- Transformers 4.42.4 |
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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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