Update README.md

How To Use
'''
from transformers import AutoImageProcessor,AutoModelForImageClassification

from PIL import Image
import requests

url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
image = Image.open(requests.get(url, stream=True).raw)

processor = AutoImageProcessor.from_pretrained('Dricz/food-classifier-224')
model = AutoForImageClassification.from_pretrained('Dricz/food-classifier-224')

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)
logits = outputs.logits
# model predicts one of the 101 food101 classes
predicted_class_idx = logits.argmax(-1).item()
print("Predicted class:", model.config.id2label[predicted_class_idx])
'''

README.md

@@ -13,76 +13,32 @@ This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the f
 <!-- Provide a quick summary of what the model is/does. -->
 <ul>Evaluation loss: 0.7166455984115601</ul>
 <ul>Accuracy: 0.8753663366336634</ul>
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
 
-## Model Details
 
+## Model Details
+A model that can detect 101 variety of food.
 ### Model Description
 
 <!-- Provide a longer summary of what this model is. -->
 
 
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+- **Developed by:** Dricz
+- **Model type:** Image classification
+- **Language(s) (NLP):** English
+- **Finetuned from model:** google/vit-base-patch16-224-in21k
 
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
 
 ## Training Details
 
 ### Training Data
-
+-**training_loss:** 1.
+-**train_runtime:** 3538
+-**train_samples_per_second:** 21.409
+-**train_steps_per_second:** 1.338
+-**total_flos:** 5.8752267138432e+18
+-**train_loss:** 1.7299224627936907
+-**epoch:** 1.0
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
 
 [More Information Needed]
@@ -98,110 +54,25 @@ Use the code below to get started with the model.
 
 #### Training Hyperparameters
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+The following hyperparameters were used during training:
 
-#### Speeds, Sizes, Times [optional]
-TrainOutput(global_step=4735, training_loss=1.7299224627936907, metrics={'train_runtime': 3538.2995, 'train_samples_per_second': 21.409, 'train_steps_per_second': 1.338, 'total_flos': 5.8752267138432e+18, 'train_loss': 1.7299224627936907, 'epoch': 1.0})
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+-**learning_rate:** 5e-05
+-**train_batch_size**: 16
+-**eval_batch_size:** 16
+-**seed:** 42
+-**optimizer:** Adam with betas=(0.9,0.999) and epsilon=1e-08
+-**lr_scheduler_type:** linear
+-**num_epochs:** 1
 
 [More Information Needed]
 
 ## Evaluation
 
 <!-- This section describes the evaluation protocols and provides the results. -->
-eval_loss: 0.7166455984115601
-eval_accuracy: 0.8753663366336634, 'eval_runtime': 446.9362, 'eval_samples_per_second': 56.496, 'eval_steps_per_second': 3.533, 'epoch': 1.0
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
+-**eval_loss:** 0.7166455984115601
+-**eval_accuracy:** 0.8753663366336634 
+-**eval_runtime:** 446.9362
+-**eval_samples_per_second:** 56.496 
+-**eval_steps_per_second:** 3.533 
+-**epoch:** 1.0
 
-[More Information Needed]