Update README.md

README.md

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 ---
 license: apache-2.0
+tags:
+- image-captioning
+languages:
+- en
+pipeline_tag: image-to-text
+datasets:
+- michelecafagna26/hl
+language:
+- en
+metrics:
+- sacrebleu
+- rouge
+library_name: transformers
 ---
+## BLIP-base fine-tuned for Image Capioning on High-Level descriptions of Actons
+
+[BLIP](https://arxiv.org/abs/2201.12086) base trained on the [HL dataset](https://huggingface.co/datasets/michelecafagna26/hl) for **high-level descriptions of actions**
+
+## Model fine-tuning 🏋️‍
+
+Trained for a maximum of 6 epochs using a
+lr:  5e−5,
+Adam optimizer,
+half-precision (fp16)
+
+## Test set metrics 🧾
+
+    | Cider  | SacreBLEU  | Rouge-L|
+    |--------|------------|--------|
+    | 123.07 |    17.16   |  32.16 |
+
+## Model in Action 🚀
+
+```python
+import requests
+from PIL import Image
+from transformers import BlipProcessor, BlipForConditionalGeneration
+
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base").to("cuda")
+
+img_url = 'https://datasets-server.huggingface.co/assets/michelecafagna26/hl/--/default/train/0/image/image.jpg' 
+raw_image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
+
+
+inputs = processor(raw_image, return_tensors="pt").to("cuda")
+pixel_values = inputs.pixel_values
+
+generated_ids = model.generate(pixel_values=pixel_values, max_length=50,
+            do_sample=True,
+            top_k=120,
+            top_p=0.9,
+            early_stopping=True,
+            num_return_sequences=1)
+
+processor.batch_decode(generated_ids, skip_special_tokens=True)
+
+>>> she's holding a parasol
+```
+
+## BibTex and citation info
+
+```BibTeX
+```