Adding more information to the model card.

README.md

@@ -201,13 +201,54 @@ library_name: transformers
 # whisper-large-v3-ca-3catparla
 - **Paper:** [3CatParla: A New Open-Source Corpus of Broadcast TV in Catalan for Automatic Speech Recognition](https://iberspeech.tech/)
 
+## Table of Contents
+<details>
+<summary>Click to expand</summary>
+
+- [Model description](#model-description)
+- [Intended uses and limitations](#intended-uses-and-limitations)
+- [How to use](#how-to-use)
+- [Training](#training)
+- [Evaluation](#evaluation)
+- [Citation](#citation)
+- [Additional information](#additional-information)
+
+</details>
+
+## Summary
+
+The "whisper-large-v3-ca-3catparla" is an acoustic model based on ["openai/whisper-large-v3"](https://huggingface.co/openai/whisper-large-v3) suitable for Automatic Speech Recognition in Catalan.
+
+## Model Description
+
 The "whisper-large-v3-ca-3catparla" is an acoustic model suitable for Automatic Speech Recognition in Catalan. It is the result of finetuning the model ["openai/whisper-large-v3"](https://huggingface.co/openai/whisper-large-v3) with 710 hours of Catalan data released by the [Projecte AINA](https://projecteaina.cat/) from Barcelona, Spain.
 
-The specific dataset used to create the model is called ["3CatParla"](https://huggingface.co/datasets/projecte-aina/3catparla_asr).
+## Intended Uses and Limitations
+
+This model can used for Automatic Speech Recognition (ASR) in Catalan. The model is intended to transcribe audio files in Catalan to plain text without punctuation.
 
-The fine-tuning process was perform during July (2024) in the servers of the [Barcelona Supercomputing Center](https://www.bsc.es/) by [Carlos Daniel Hernández Mena](https://huggingface.co/carlosdanielhernandezmena).
+## How to Get Started with the Model
+
+### Installation
+
+In order to use this model, you may install [datasets](https://huggingface.co/docs/datasets/installation) and [transformers](https://huggingface.co/docs/transformers/installation):
+
+Create a virtual environment:
+```bash
+python -m venv /path/to/venv
+```
+Activate the environment:
+```bash
+source /path/to/venv/bin/activate
+```
+Install the modules:
+```bash
+pip install datasets transformers 
+```
+
+### For Inference
+In order to transcribe audio in Catalan using this model, you can follow this example:
 
-# Evaluation
 ```python
 import torch
 from transformers import WhisperForConditionalGeneration, WhisperProcessor
@@ -250,8 +291,34 @@ print(WER)
 ```
 **Test Result**: 0.96
 
-# BibTeX entry and citation info
-* When publishing results based on these models please refer to:
+## Training Details
+
+### Training data
+
+The specific dataset used to create the model is called ["3CatParla"](https://huggingface.co/datasets/projecte-aina/3catparla_asr).
+
+### Training procedure
+
+This model is the result of finetuning the model ["openai/whisper-large-v3"](https://huggingface.co/openai/whisper-large-v3) by following this [tutorial](https://huggingface.co/blog/fine-tune-whisper) provided by Hugging Face.
+
+### Training Hyperparameters
+
+* language: catalan
+* hours of training audio: 710
+* learning rate: 1.95e-07
+* sample rate: 16000
+* train batch size: 32 (x4 GPUs)
+  * gradient accumulation steps: 1
+* eval batch size: 32
+* save total limit: 3
+* max steps: 19842
+* warmup steps: 1984
+* eval steps: 3307
+* save steps: 3307
+* shuffle buffer size: 480
+
+## Citation
+If this code contributes to your research, please cite the work:
 ```bibtex
 @misc{mena2024whisperlarge3catparla,
       title={Acoustic Model in Catalan: whisper-large-v3-ca-3catparla.}, 
@@ -261,6 +328,24 @@ print(WER)
       year={2024}
 }
 ```
-# Acknowledgements
 
-This model has been promoted and financed by the Government of Catalonia through the Aina project.
+## Additional Information
+
+### Author
+
+The fine-tuning process was perform during July (2024) in the [Language Technologies Unit](https://huggingface.co/BSC-LT) of the [Barcelona Supercomputing Center](https://www.bsc.es/) by [Carlos Daniel Hernández Mena](https://huggingface.co/carlosdanielhernandezmena).
+
+### Contact
+For further information, please send an email to <[email protected]>.
+
+### Copyright
+Copyright(c) 2024 by Language Technologies Unit, Barcelona Supercomputing Center.
+
+### License
+
+[Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)
+
+### Funding
+This work has been promoted and financed by the Generalitat de Catalunya through the [Aina project](https://projecteaina.cat/).
+
+The training of the model was possible thanks to the compute time provided by [Barcelona Supercomputing Center](https://www.bsc.es/) through MareNostrum 5.