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README.md
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model-index:
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- name: prosody_gttbsc_distilbert-uncased-best
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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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# prosody_gttbsc_distilbert-uncased-best
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## Model description
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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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## 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.
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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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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### Framework versions
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- generated_from_trainer
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model-index:
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- name: prosody_gttbsc_distilbert-uncased-best
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results:
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- task:
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type: dialogue act classification
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dataset:
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name: asapp/slue-phase-2
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type: hvb
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metrics:
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- name: F1 macro E2E
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type: F1 macro
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value: 66.43
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- name: F1 macro GT
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type: F1 macro
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value: 72.70
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datasets:
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- asapp/slue-phase-2
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language:
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- en
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metrics:
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- f1-macro
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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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# prosody_gttbsc_distilbert-uncased-best
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Ground truth text with prosody encoding cross attention multi-label DAC
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## Model description
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Prosody encoder: 2 layer transformer encoder with initial dense projection
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Backbone: [DistilBert uncased](https://huggingface.co/distilbert/distilbert-base-uncased)
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Pooling: Self attention
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Multi-label classification head: 2 dense layers with two dropouts 0.3 and Tanh activation inbetween
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## Training and evaluation data
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Trained on ground truth [slue-phase-2 hvb](https://huggingface.co/datasets/asapp/slue-phase-2).
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Evaluated on ground truth and normalized [Whisper small](https://huggingface.co/openai/whisper-small) transcripts.
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0004
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- num_epochs: 20
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- mixed_precision_training: Native AMP
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### Framework versions
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