Update README.md

README.md

@@ -1,74 +1,309 @@
----
-license: apache-2.0
-language:
-- en
-pipeline_tag: text2text-generation
-tags:
-- 文本
-metrics:
-- accuracy
-library_name: adapter-transformers
----
-# Model Card for SG0.1.pth
+# Model Card for SG0.1
 
-## Model Details
+<!-- Provide a quick summary of what the model is/does. [Optional] -->
+{
+    &#34;license&#34;: &#34;apache-2.0&#34;,
+    &#34;language&#34;: [&#34;en&#34;],
+    &#34;metrics&#34;: [&#34;accuracy&#34;, &#34;bertscore&#34;],
+    &#34;library_name&#34;: [&#34;adapter-transformers&#34;, &#34;transformers&#34;],
+    &#34;model_name&#34;: &#34;AutoModel&#34;,
+    &#34;model_type&#34;: &#34;multimodal-transformer&#34;,
+    &#34;tags&#34;: [&#34;multimodal&#34;, &#34;transformer&#34;],
+    &#34;datasets&#34;: [&#34;dataset1&#34;, &#34;dataset2&#34;],
+    &#34;finetuned_from&#34;: &#34;pretrained-model&#34;,
+    &#34;config&#34;: {
+        &#34;hidden_size&#34;: 768,
+        &#34;num_attention_heads&#34;: 12,
+        &#34;num_hidden_layers&#34;: 12,
+        &#34;intermediate_size&#34;: 2048,
+        &#34;hidden_dropout_prob&#34;: 0.1,
+        &#34;attention_probs_dropout_prob&#34;: 0.1,
+        &#34;image_size&#34;: 224,
+        &#34;image_channels&#34;: 3,
+        &#34;patch_size&#34;: 16,
+        &#34;max_position_embeddings&#34;: 512,
+        &#34;vocab_size&#34;: 30522,
+        &#34;type_vocab_size&#34;: 2,
+        &#34;audio_sample_rate&#34;: 16000,
+        &#34;audio_frame_size&#34;: 1024,
+        &#34;audio_hop_size&#34;: 512,
+        &#34;enable_vqa&#34;: True,
+        &#34;enable_caption&#34;: True,
+        &#34;enable_retrieval&#34;: True,
+        &#34;enable_asr&#34;: True,
+        &#34;enable_realtime_asr&#34;: True,
+        &#34;batch_size&#34;: 32,
+        &#34;learning_rate&#34;: 0.0001,
+        &#34;weight_decay&#34;: 0.01,
+        &#34;warmup_steps&#34;: 10000,
+        &#34;max_steps&#34;: 100000
+    }
+}
 
-### Model Description
 
-This model, named SG0.1.pth, is a multimodal transformer designed to handle a variety of tasks including vision and audio processing. It is built on top of the adapter-transformers and transformers libraries and is intended to be a versatile base model for both direct use and fine-tuning.
 
-**Developed by:** Independent researcher
-**Funded by :** Self-funded
-**Shared by :** Independent researcher
-**Model type:** Multimodal
-**Language(s) (NLP):** English zh
-**License:** Apache-2.0
-**Finetuned from model :** None
 
-### Model Sources
+#  Table of Contents
 
-**Repository:** [GitHub Repository Placeholder](https://huggingface.co/zeroMN/SG1.0) *(Add link to code repository)*
-**Paper [optional]:** 
-**Demo [optional]:** 
+- [Model Card for SG0.1](#model-card-for--model_id-)
+- [Table of Contents](#table-of-contents)
+- [Table of Contents](#table-of-contents-1)
+- [Model Details](#model-details)
+  - [Model Description](#model-description)
+- [Uses](#uses)
+  - [Direct Use](#direct-use)
+  - [Downstream Use [Optional]](#downstream-use-optional)
+  - [Out-of-Scope Use](#out-of-scope-use)
+- [Bias, Risks, and Limitations](#bias-risks-and-limitations)
+  - [Recommendations](#recommendations)
+- [Training Details](#training-details)
+  - [Training Data](#training-data)
+  - [Training Procedure](#training-procedure)
+    - [Preprocessing](#preprocessing)
+    - [Speeds, Sizes, Times](#speeds-sizes-times)
+- [Evaluation](#evaluation)
+  - [Testing Data, Factors & Metrics](#testing-data-factors--metrics)
+    - [Testing Data](#testing-data)
+    - [Factors](#factors)
+    - [Metrics](#metrics)
+  - [Results](#results)
+- [Model Examination](#model-examination)
+- [Environmental Impact](#environmental-impact)
+- [Technical Specifications [optional]](#technical-specifications-optional)
+  - [Model Architecture and Objective](#model-architecture-and-objective)
+  - [Compute Infrastructure](#compute-infrastructure)
+    - [Hardware](#hardware)
+    - [Software](#software)
+- [Citation](#citation)
+- [Glossary [optional]](#glossary-optional)
+- [More Information [optional]](#more-information-optional)
+- [Model Card Authors [optional]](#model-card-authors-optional)
+- [Model Card Contact](#model-card-contact)
+- [How to Get Started with the Model](#how-to-get-started-with-the-model)
 
-## Uses
 
-### Direct Use
+# Model Details
 
-The `SG0.1.pth` model can be used directly for tasks such as image classification, object detection, and audio processing without any fine-tuning. It is designed to handle a wide range of input modalities and can be integrated into various applications.
+## Model Description
 
-### Downstream Use
+<!-- Provide a longer summary of what this model is/does. -->
+{
+    &#34;license&#34;: &#34;apache-2.0&#34;,
+    &#34;language&#34;: [&#34;en&#34;],
+    &#34;metrics&#34;: [&#34;accuracy&#34;, &#34;bertscore&#34;],
+    &#34;library_name&#34;: [&#34;adapter-transformers&#34;, &#34;transformers&#34;],
+    &#34;model_name&#34;: &#34;AutoModel&#34;,
+    &#34;model_type&#34;: &#34;multimodal-transformer&#34;,
+    &#34;tags&#34;: [&#34;multimodal&#34;, &#34;transformer&#34;],
+    &#34;datasets&#34;: [&#34;dataset1&#34;, &#34;dataset2&#34;],
+    &#34;finetuned_from&#34;: &#34;pretrained-model&#34;,
+    &#34;config&#34;: {
+        &#34;hidden_size&#34;: 768,
+        &#34;num_attention_heads&#34;: 12,
+        &#34;num_hidden_layers&#34;: 12,
+        &#34;intermediate_size&#34;: 2048,
+        &#34;hidden_dropout_prob&#34;: 0.1,
+        &#34;attention_probs_dropout_prob&#34;: 0.1,
+        &#34;image_size&#34;: 224,
+        &#34;image_channels&#34;: 3,
+        &#34;patch_size&#34;: 16,
+        &#34;max_position_embeddings&#34;: 512,
+        &#34;vocab_size&#34;: 30522,
+        &#34;type_vocab_size&#34;: 2,
+        &#34;audio_sample_rate&#34;: 16000,
+        &#34;audio_frame_size&#34;: 1024,
+        &#34;audio_hop_size&#34;: 512,
+        &#34;enable_vqa&#34;: True,
+        &#34;enable_caption&#34;: True,
+        &#34;enable_retrieval&#34;: True,
+        &#34;enable_asr&#34;: True,
+        &#34;enable_realtime_asr&#34;: True,
+        &#34;batch_size&#34;: 32,
+        &#34;learning_rate&#34;: 0.0001,
+        &#34;weight_decay&#34;: 0.01,
+        &#34;warmup_steps&#34;: 10000,
+        &#34;max_steps&#34;: 100000
+    }
+}
 
-The model can be fine-tuned for specific tasks such as visual question answering (VQA), image captioning, and audio recognition. It is particularly useful for multimodal tasks that require understanding both visual and audio inputs.
+- **Developed by:** More information needed
+- **Shared by [Optional]:** More information needed
+- **Model type:** Language model
+- **Language(s) (NLP):** en, zh
+- **License:** apache-2.0
+- **Parent Model:** More information needed
+- **Resources for more information:** More information needed
 
-### Out-of-Scope Use
 
-The `SG0.1.pth` model is not designed for tasks that require highly specialized knowledge or domain-specific expertise beyond its current capabilities. It may not perform well on tasks that require fine-grained recognition or highly specialized audio processing.
 
-## Bias, Risks, and Limitations
+# Uses
 
-### Recommendations
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-Users (both direct and downstream) should be made aware of the following risks, biases, and limitations:
+## Direct Use
 
-- **Bias:** The model may exhibit biases present in the training data, particularly if the data is not representative of all populations.
-- **Risks:** The model should not be used in critical applications where high accuracy and reliability are required without thorough testing and validation.
-- **Limitations:** The model may not perform well on tasks that require fine-grained recognition or highly specialized audio processing.
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
 
-## How to Get Started with the Model
 
-Use the code below to get started with the `SG0.1.pth` model.
 
-```python
-import torch
 
-# Load the model
-model = torch.load('path/to/SG1.0.pth')
-model.eval()
+## Downstream Use [Optional]
 
-# Example input
-dummy_input = torch.randn(1, 3, 224, 224)  # Example input for image processing
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
+ 
 
-# Forward pass
-output = model(dummy_input)
-print(output)
+
+
+## Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
+
+
+
+
+# Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
+
+
+## Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+
+
+
+
+# Training Details
+
+## Training Data
+
+<!-- This should link to a Data 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 on training data needed
+
+
+## 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
+
+More information needed
+
+### Speeds, Sizes, Times
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+More information needed
+ 
+# Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+## Testing Data, Factors & Metrics
+
+### Testing Data
+
+<!-- This should link to a Data 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
+
+# Model Examination
+
+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
+
+<!-- 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]
+
+<!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. -->
+
+zero
+
+# Model Card Contact
+
+More information needed
+
+# How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+<details>
+<summary> Click to expand </summary>
+
+More information needed
+
+</details>