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  model-index:
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  - name: wav2vec-best-CREMA-sentiment-analysis-best3
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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
@@ -15,25 +17,15 @@ should probably proofread and complete it, then remove this comment. -->
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  # wav2vec-best-CREMA-sentiment-analysis-best3
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- This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Top2 Accuracy: 0.7824
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  - Loss: 1.1563
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  - Accuracy: 0.5601
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  ## Model description
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- More information needed
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- ## Intended uses & limitations
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-
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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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  - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  model-index:
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  - name: wav2vec-best-CREMA-sentiment-analysis-best3
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  results: []
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+ datasets:
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+ - Supreeta03/CREMA-audioData
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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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  # wav2vec-best-CREMA-sentiment-analysis-best3
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on [Supreeta03/CREMA-audioData](https://huggingface.co/datasets/Supreeta03/CREMA-audioData).
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  It achieves the following results on the evaluation set:
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+ - top2 Accuracy: 0.7824
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  - Loss: 1.1563
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  - Accuracy: 0.5601
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  ## Model description
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+ Fine tuned from [facebook/wav2vec2-base] for performing sentiment analysis on audio data.
 
 
 
 
 
 
 
 
 
 
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  ### Training hyperparameters
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  - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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+ - Tokenizers 0.15.2