model documentation

README.md

@@ -1,11 +1,161 @@
----
-language: en
-license: cc-by-nc-sa-4.0
-tags:
- - layoutlm
- - document-classification
- - pdf
- - invoices
----
+ # Model Card for LayoutLM for Document Classification
+ 
+# Model Details
+ 
+## Model Description
+ 
+This is a fine-tuned version of the multi-modal LayoutLM model for the task of classification on documents. 
+ 
+ 
+- **Developed by:** Impira team
+- **Shared by [Optional]:** Hugging Face
+- **Model type:** Text Classification
+- **Language(s) (NLP):** en
+- **License:** cc-by-nc-sa-4.0
+- **Related Models:** layoutlm
+  - **Parent Model:** More information needed
+- **Resources for more information:** 
+  - [Associated Paper](https://arxiv.org/abs/1912.13318) 
+  - [Blog Post](https://www.impira.com/blog/introducing-instant-invoices)
+ 
+# Uses
+ 
+ 
+## Direct Use
+ 
+Text Classification
+ 
+## Downstream Use [Optional]
+ 
+More information needed
+ 
+## Out-of-Scope Use
+ 
+The model should not be used to intentionally create hostile or alienating environments for people. 
+# Bias, Risks, and 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
+ 
+ 
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+ 
+ 
+# Training Details
+ 
+## Training Data
+ 
+More information needed
+ 
+## Training Procedure
+ 
+More information needed
+ 
+### Preprocessing
+ 
+More information needed
+ 
+### Speeds, Sizes, Times
+ 
+Num_attention_head: 12
+Num_hidden_layer:12,
+Vocab_size: 30522
+ 
+# Evaluation
+ 
+## Testing Data, Factors & Metrics
+ 
+### Testing Data
+ 
+More information needed
+ 
+### Factors
+More information needed
+ 
+### Metrics
+ 
+More information needed
+ 
+## Results 
+ 
+More information needed
+ 
+# Model Examination
+ 
+More information needed
+ 
+# Environmental Impact
+ 
+ 
+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
+Transformers  version: 4.4.0.dev0
 
-TODO
+# Citation
+ 
+ 
+**BibTeX:**
+ 
+More information needed}
+ 
+**APA:**
+ 
+More information needed
+ 
+# Glossary [optional]
+ 
+More information needed
+ 
+# More Information [optional]
+ 
+More information needed
+ 
+# Model Card Authors [optional]
+Impira team in collaboration with Ezi Ozoani and the Hugging Face team.
+ 
+# 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>
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+ 
+tokenizer = AutoTokenizer.from_pretrained("impira/layoutlm-document-classifier")
+ 
+model = AutoModelForSequenceClassification.from_pretrained("impira/layoutlm-document-classifier")
+ 
+ ```
+</details>
+ 
+ 
+