Update README.md

README.md

@@ -56,29 +56,28 @@ This modelcard aims to be a base template for new models. It has been generated
 
 [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]
-
-### Recommendations
+## How to Get Started with the Model
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+```python
+import torch
+from transformers import BertForSequenceClassification, BertTokenizer
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+# Load model and tokenizer
+model = BertForSequenceClassification.from_pretrained("scfengv/TVL_GeneralLayerClassifier")
+tokenizer = BertTokenizer.from_pretrained("scfengv/TVL_GeneralLayerClassifier")
 
-## How to Get Started with the Model
+# Prepare your text
+text = "Your text here"
+inputs = tokenizer(text, return_tensors = "pt", padding = True, truncation = True, max_length = 512)
 
-Use the code below to get started with the model.
+# Make prediction
+with torch.no_grad():
+    outputs = model(**inputs)
+    predictions = torch.sigmoid(outputs.logits)
 
-[More Information Needed]
+# Print predictions
+print(predictions)
+```
 
 ## Training Details
 
@@ -90,7 +89,6 @@ Use the code below to get started with the model.
 
 ### Training Procedure
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
 
 #### Preprocessing [optional]
 
@@ -99,7 +97,13 @@ 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 model was trained using the following hyperparameters:
+
+Learning rate: 1e-05
+Batch size: 32
+Number of epochs: 10
+Optimizer: Adam
 
 #### Speeds, Sizes, Times [optional]
 
@@ -133,7 +137,9 @@ Use the code below to get started with the model.
 
 ### Results
 
-[More Information Needed]
+- Accuracy: 0.9592504607823059
+- F1 Score (Micro): 0.9740588950133884
+- F1 Score (Macro): 0.9757074189160264
 
 #### Summary
 
@@ -145,18 +151,6 @@ Use the code below to get started with the model.
 
 [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
@@ -175,24 +169,6 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 [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]