Training in progress, step 3050

README.md

@@ -14,12 +14,6 @@ pipeline_tag: image-to-text
 
 ![Stage](https://img.shields.io/badge/stage-early%20development-yellow)![License](https://img.shields.io/badge/license-Apache%202.0-blue)![Contributors Welcome](https://img.shields.io/badge/contributors-welcome-brightgreen)[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb)
 
-## Star the project
-
-**If you appreciate my work, please consider giving it a star! 🤩**  
-**I'm also looking for donations of free GPU time to complete the fine-tuning process.**  
-**Please contact me if you can help! 🙏**  
-
 ## A Fine-tuned Radiology-focused Model based on Hugging Face's Idefics3 Model
 
 This repository contains a fine-tuned version of the Hugging Face [Idefics3-8B-Llama3](https://huggingface.co/HuggingFaceM4/Idefics3-8B-Llama3) model, built on top of the Meta Llama 3.1 8B architecture. Our model, `IDEFICS3_ROCO`, has been fine-tuned on the [Radiology Objects in Context (ROCO)](https://huggingface.co/datasets/eltorio/ROCO-radiology) dataset, a large-scale medical and multimodal imaging collection.
@@ -33,7 +27,7 @@ This repository contains a fine-tuned version of the Hugging Face [Idefics3-8B-L
 
 ### Training Progress Status
 
-* Current checkpoint: 3000/12267 (~25% completed)
+* Current checkpoint: 2350/12267 (~19% completed) (in branch bug-restart)
 * Estimated remaining GPU time: ~57 hours
 * Hardware requirements: T4 GPU with >16GB VRAM
 * Last update: november, 8th 2024
@@ -66,7 +60,7 @@ If you use this model in your work, please cite the original Idefics3 model and
 
 2. **Getting Started**
    * Fork the repository
-   * Resume from checkpoint 3000/12267
+   * Resume from checkpoint 2350/12267 (in branch bug-restart)
    * Follow instructions in [ROCO-idefics3.ipynb](https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb)
 
 3. **Contact**
@@ -74,15 +68,10 @@ If you use this model in your work, please cite the original Idefics3 model and
 
 ### Docker Image
 
-A AI training docker image is available for this model. The image and includes all necessary dependencies to run the fine-tuning process.  
-You need to set the `HF_TOKEN` environment variable to your Hugging Face API token.  
-You also need to have NVidia Docker container runtime installed.
-Finnaly, you need to run the container with GPU support with `--gpus all` option.
-The image is available on Docker Hub:  
+A AI training docker image is available for this model. The image and includes all necessary dependencies to run the fine-tuning process. The image is available on Docker Hub:  
 
 ```bash
-export HF_TOKEN=hf_some_token
-docker run --gpus all --user=42420:42420 -e HF_TOKEN=$HF_TOKEN -it sctg/roco-idefics3:latest bash -i  /start.sh $HF_TOKEN
+docker run --user=42420:42420 -it sctg/roco-idefics3:latest /start.sh hf_TOKEN
 ```
 
 The Dockerfile is available in the [IDEFICS_ROCO repository](https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/Dockerfile).

adapter_model.safetensors

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