Create README.md

README.md

@@ -0,0 +1,59 @@
+---
+language: es
+tags:
+ - Spanish
+ - Electra
+ - Bio
+ - Medical
+
+datasets:
+ - cowese
+---
+
+## BIOMEDTRA 🦠🏥
+
+**BIOMEDTRA** (small) is an Electra like model (discriminator in this case) trained on [Spanish Biomedical Crawled Corpus](https://zenodo.org/record/5510033#.Yhdk1ZHMLJx).
+
+As mentioned in the original [paper](https://openreview.net/pdf?id=r1xMH1BtvB):
+**ELECTRA** is a new method for self-supervised language representation learning. It can be used to pre-train transformer networks using relatively little compute. ELECTRA models are trained to distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to the discriminator of a [GAN](https://arxiv.org/pdf/1406.2661.pdf). At small scale, ELECTRA achieves strong results even when trained on a single GPU. At large scale, ELECTRA achieves state-of-the-art results on the [SQuAD 2.0](https://rajpurkar.github.io/SQuAD-explorer/) dataset.
+
+For a detailed description and experimental results, please refer the paper [ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators](https://openreview.net/pdf?id=r1xMH1BtvB).
+
+
+## Training details
+
+The model was trained using the Electra base code for 3 days on 1 Tesla V100 16GB.
+
+## Model details ⚙
+
+|Param| # Value|
+|-----|--------|
+|Layers| 12 |
+|Hidden | 256 |
+|Params| 14M |
+
+## Evaluation metrics (for discriminator) 🧾
+
+|Metric | # Score |
+|-------|---------|
+|Accuracy| 0.955|
+|Precision| 0.790|
+|AUC | 0.971|
+
+
+## Benchmarks 🔨
+
+WIP 🚧
+
+## How to use the discriminator in `transformers`
+
+TBA
+
+## Acknowledgments
+
+TBA
+
+
+> Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488)
+
+> Made with <span style="color: #e25555;">&hearts;</span> in Spain