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  ### Model Summary
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- CLIP_TROHN-Text is a model presented in the [BiVLC](https://github.com/IMirandaM/BiVLC) paper for experimentation. It has been fine-tuned with OpenCLIP framework using as basis the CLIP ViT-B-32 model pre-trained by 'openai'. Hyperparameters:
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  * Learning rate: 1e-6.
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  * Scheduler: Cosine scheduler with 50 warmup steps.
 
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  ### Model Summary
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+ CLIP_TROHN-Text is a model presented in the [BiVLC](https://github.com/IMirandaM/BiVLC) paper for experimentation. It has been fine-tuned with OpenCLIP framework using as basis the CLIP ViT-B-32 model pre-trained by 'openai'. The idea behind this fine-tuning is to improve the compositional understanding of the model by adding negative captions. The negatives present small compositional changes. Hyperparameters:
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  * Learning rate: 1e-6.
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  * Scheduler: Cosine scheduler with 50 warmup steps.