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README.md

@@ -1,9 +1,13 @@
 ---
-library_name: transformers
-tags: []
+language: en
+tags:
+- text-classification
+tasks:
+- text-classification
+dataset_name: New
 ---
 
-# Model Card for Model ID
+# Model Card for acuvity/model_integration_test
 
 <!-- Provide a quick summary of what the model is/does. -->
 
@@ -15,21 +19,21 @@ tags: []
 
 <!-- Provide a longer summary of what this model is. -->
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+Auto Fine-tuned acuvity/model_integration_test for text-classification task. The run id is v0.0.2
 
-- **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]
+- **Developed by:** Auto-Finetune Bot
+- **Funded by [optional]:** Auto-Finetune Bot
+- **Shared by [optional]:** Auto-Finetune Bot
+- **Model type:** text-classification
+- **Language(s) (NLP):** en
+- **License:** Closed Source
+- **Finetuned from model [optional]:** acuvity/model_integration_test
 
 ### Model Sources [optional]
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
+- **Repository:** [acuvity/model_integration_test](https://huggingface.co/acuvity/acuvity/model_integration_test)
 - **Paper [optional]:** [More Information Needed]
 - **Demo [optional]:** [More Information Needed]
 
@@ -71,7 +75,27 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 
 Use the code below to get started with the model.
 
-[More Information Needed]
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("acuvity/model_integration_test")
+model = AutoModelForSequenceClassification.from_pretrained("acuvity/model_integration_test")
+
+inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
+with torch.no_grad():
+    logits = model(**inputs).logits
+
+predicted_class_id = logits.argmax().item()
+model.config.id2label[predicted_class_id]
+```
+```python
+from transformers import pipeline
+classifier = pipeline("text-classification", model="acuvity/model_integration_test")
+classifier("Hello, my dog is cute")
+```
+    
 
 ## Training Details
 
@@ -79,7 +103,7 @@ Use the code below to get started with the model.
 
 <!-- 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]
+(New | v0.0.2) [https://huggingface.co/datasets/acuvity/New]
 
 ### Training Procedure
 
@@ -87,12 +111,12 @@ Use the code below to get started with the model.
 
 #### Preprocessing [optional]
 
-[More Information Needed]
+No modifications done on the dataset.
 
 
 #### 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 -->
+- **Training regime:** {'fp16_bool': False, 'num_train_epochs': 5, 'learning_rate': 1e-05, 'batch_size': 256, 'weight_decay': 0.01} <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
 
 #### Speeds, Sizes, Times [optional]
 
@@ -110,7 +134,7 @@ Use the code below to get started with the model.
 
 <!-- This should link to a Dataset Card if possible. -->
 
-[More Information Needed]
+(New | v0.0.2) [https://huggingface.co/datasets/acuvity/New]
 
 #### Factors
 
@@ -126,7 +150,41 @@ Use the code below to get started with the model.
 
 ### Results
 
-[More Information Needed]
+
+# Auto Finetune Report for Prompt Injection
+## Model URL: acuvity/model_integration_test
+## Model Commit: v0.0.2
+
+## Quick Summary
+
+Accuracy: 0.014995313964386137
+Regression: 0.030901660532351393
+Improvement: 0.14807888125828456
+
+## Results Summary
+
+### Prompt Injection | v0.0.2 Results
+
+|          |   accuracy |        f1 |   precision |   recall |
+|:---------|-----------:|----------:|------------:|---------:|
+| New      |  0.996251  | 0.995984  |   1         | 0.992    |
+| Baseline |  0.998     | 0.997988  |   1         | 0.995984 |
+| Feedback |  0.833333  | 0         |   0         | 0        |
+| QA       |  0.980398  | 0         |   0         | 0        |
+| PINT     |  0.0804789 | 0.0972902 |   0.0523726 | 0.683486 |
+| Sanity   |  0.652174  | 0.789474  |   0.652174  | 1        |
+----------------------------------------------------
+### Prompt Injection | v0.0.1 Results
+|          |   accuracy |       f1 |   precision |   recall |
+|:---------|-----------:|---------:|------------:|---------:|
+| New      |   0.981256 | 0.980159 |   0.995968  | 0.964844 |
+| Baseline |   0.993    | 0.992965 |   0.995968  | 0.98998  |
+| Feedback |   0        | 0        |   0         | 0        |
+| QA       |   0.973455 | 0        |   0         | 0        |
+| PINT     |   0.122049 | 0.175515 |   0.0987698 | 0.787115 |
+| Sanity   |   0.76087  | 0.864198 |   0.76087   | 1        |
+
+    
 
 #### Summary
 
@@ -144,29 +202,41 @@ Use the code below to get started with the model.
 
 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]
+- **Hardware Type:** Quadro P4000
+- **Hours used:** 4 Hours
+- **Cloud Provider:** Paperspace | Digital Ocean
+- **Compute Region:** NY2
+- **Carbon Emitted:** 0, we are carbon neutral
 
 ## Technical Specifications [optional]
 
 ### Model Architecture and Objective
 
-[More Information Needed]
+acuvity/model_integration_test
 
 ### Compute Infrastructure
 
-[More Information Needed]
+|                  | 0                                            |
+|:-----------------|:---------------------------------------------|
+| platform         | Linux                                        |
+| platform-release | 5.15.0-130-generic                           |
+| platform-version | #140-Ubuntu SMP Wed Dec 18 17:59:53 UTC 2024 |
+| architecture     | x86_64                                       |
+| processor        | x86_64                                       |
+| ram              | 29 GB                                        |
 
 #### Hardware
 
-[More Information Needed]
+Quadro P4000
 
 #### Software
 
-[More Information Needed]
+|                      | 0           |
+|:---------------------|:------------|
+| python_version       | 3.10.12     |
+| pytorch_version      | 2.1.2+cu121 |
+| transformers_version | 4.49.0      |
+| datasets_version     | 3.2.0       |
 
 ## Citation [optional]
 
@@ -192,8 +262,8 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ## Model Card Authors [optional]
 
-[More Information Needed]
+acuvity
 
 ## Model Card Contact
 
-[More Information Needed]
+[[email protected]](mailto:[email protected])