[ADD] Tools, Framework License and Citation Information sections

README.md

@@ -34,25 +34,25 @@ widget:
   - [Intended uses and limitations](#intended-uses-and-limitations)
   - [How to use](#how-to-use)
   - [Training](#training)
-    - [Platform](#platform)
+    - [Tools](#tools)
     - [Language adaptation and training](#language-adaptation-and-training)
     - [Training data](#training-data)
     - [Training hyperparameters](#training-hyperparameters)
     - [Framework](#framework)
   - [Evaluation](#evaluation)
   - [Additional information](#additional-information)
-    - [Author](#author)
     - [Contact](#contact)
     - [Copyright](#copyright)
     - [License](#license)
     - [Funding](#funding)
+  - [Citation information](#citation-information)
 
 </details>
 
 ## Model description
 
 **FLOR-1.3B-GL** is a 1.3B-parameter transformer-based causal language model for Galician. 
-It is the result of continual pretraining of [FLOR-1.3B](https://huggingface.co/projecte-aina/FLOR-1.3B) with the galician corpus [CorpusNos]().
+It is the result of a continual pretraining of [FLOR-1.3B](https://huggingface.co/projecte-aina/FLOR-1.3B) (based in [BLOOM-1.7B](https://huggingface.co/bigscience/bloom-1b7)) with the galician corpus [CorpusNos]().
 
 ## Intended uses and limitations
 
@@ -89,9 +89,9 @@ print(f"Result: {generation[0]['generated_text']}")
 
 ## Training
 
-### Platform
+### Tools
 
-HF Tranformers + run_clm.py
+It was trained using HuggingFace Transformers and Pytorch, using the [Causal Modeling Language script](https://github.com/huggingface/transformers/blob/main/examples/pytorch/language-modeling/run_clm.py)
 
 ### Language adaptation and training
 
@@ -104,6 +104,7 @@ The language adaptation technique used to train FLOR-1.3B-GL is based in the use
 
 ### Training data
 
+CorpusNos (describir) Citar paper? Zenodo?
 
 
 
@@ -121,18 +122,15 @@ The language adaptation technique used to train FLOR-1.3B-GL is based in the use
 - scheduler: "Linear" 
 - learning_rate: 5e-05
 - num_epochs: 1.2
-- 
+
 ### Framework
-CESGA, 1 node with 5GPUs A100
+The traininf was conducted in the Galicia Supercomputing Center ([CESGA](https://www.cesga.es/en/home-2/)), using 1 node with 5 GPUs NVIDIA A100.
 
 ## Evaluation
-
+ Human evaluation? Include automatic metrics? (bertscore, perplexity)
 
 ## Additional information
 
-### Author
-
-
 ### Contact
 
 
@@ -140,7 +138,23 @@ CESGA, 1 node with 5GPUs A100
 
 
 ### License
-[MIT]()
+MIT License
+
+Copyright (c) 2024 Proxecto Nós
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 
 ### Funding
-This research was funded by “The Nós project: Galician in the society and economy of Artificial Intelligence”, resulting from the agreement 2021-CP080 between the Xunta de Galicia and the University of Santiago de Compostela, and thanks to the Investigo program, within the National Recovery, Transformation and Resilience Plan, within the framework of the European Recovery Fund (NextGenerationEU).
+This research was funded by “The Nós project: Galician in the society and economy of Artificial Intelligence”, resulting from the agreement 2021-CP080 between the Xunta de Galicia and the University of Santiago de Compostela, and thanks to the Investigo program, within the National Recovery, Transformation and Resilience Plan, within the framework of the European Recovery Fund (NextGenerationEU).
+
+## Citation information
+
+If you use this model, please cite as follows:
+
+AUTHORS 
+URL: https://huggingface.co/proxectonos/FLOR-1.3B-GL
+