Update README.md

README.md

@@ -9,11 +9,9 @@ tags:
 license: apache-2.0
 ---
 
-# HelsinkiNLP-FineTuned-Legal-es-zh
-
 This model is a fine-tuned version of [Helsinki-NLP/opus-tatoeba-es-zh](https://huggingface.co/Helsinki-NLP/opus-tatoeba-es-zh) on a dataset of legal domain constructed by the author himself.
 
-## Intended uses & limitations
+# Intended uses & limitations
 
 This model is the result of the master graduation thesis for the Tradumatics: Translation Technologies program at the Autonomous University of Barcelona.
 
@@ -21,13 +19,13 @@ Please refer to GitHub repo created for this thesis for full-text and relative o
 
 The thesis intends to explain various theories and certain algorithm details about neural machine translation, thus this fine-tuned model only serves as a hands-on practice example for that objective, without any intention of productive usage.
 
-## Training and evaluation data
+# Training and evaluation data
 
 The dataset is constructed from the Chinese translation of Spanish Civil Code, Spanish Constitution, and many other laws & regulations found in the database China Law Info (北大法宝 Beida Fabao), along with their source text found on Boletín Oficial del Estado and EUR-Lex.
 
 There are 9972 sentence pairs constructed. 1000 are used for evaluation and the rest for training.
 
-## Training hyperparameters
+# Training hyperparameters
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
@@ -42,7 +40,7 @@ The following hyperparameters were used during training:
 - weight_decay: 0.01
 - early_stopping_patience: 8
 
-## Training results
+# Training results
 
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
@@ -69,7 +67,7 @@ The following hyperparameters were used during training:
 | 1.1238        | 7.49  | 8400 | 2.1102          |
 | 1.1417        | 7.84  | 8800 | 2.1078          |
 
-## Framework versions
+# Framework versions
 
 - Transformers 4.7.0
 - Pytorch 1.8.1+cu101