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README.md

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 license: apache-2.0
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+# CapDec - NoiseLevel: 0.015
+
+This is are model weights originally provided by the authors of the paper [Text-Only Training for Image Captioning using Noise-Injected CLIP](https://arxiv.org/pdf/2211.00575.pdf).
+
+There method aims to train fine-tune CLIP with only text samples. Therefore they are injecting zero-mean Gaussian Noise with a standard-deviation(STD) of into the text embeddings before decoding.
+
+In their words:
+*Specifically, we assume that the visual embedding corresponding to a text embedding 
+lies somewhere within a ball of small radius around the text embedding (see Fig. 1). 
+We would like all text embeddings in this ball to decode to the same caption,which should 
+also correspond to the visual content mapped to this ball. We implement this intuition by 
+adding zero-mean Gaussian noise of STD to the text embedding before decoding it.*
+
+The "Noise Level" of 0.015 is equivalent to the Noise Variance which is the square of the STD.
+
+The reported metrics are results of a model with a Noise Variance of 0.016, which the authors unfortunately do not provide in their repository. 
+This model with a Noise Variance 0.015 is the closest available  pre-trained model to their best model.
+