first-commit

README.md

@@ -2,36 +2,38 @@
 license: apache-2.0
 base_model: Helsinki-NLP/opus-mt-en-es
 tags:
-- generated_from_keras_callback
+- translation
+- UPV
+- MIARFID
+- EuroParl
 model-index:
 - name: dap305/Helsinki-finetuned-EuroParl-en-to-es
   results: []
+language:
+- en
+- es
+metrics:
+- bleu
+library_name: transformers
+pipeline_tag: translation
 ---
 
-<!-- This model card has been generated automatically according to the information Keras had access to. You should
-probably proofread and complete it, then remove this comment. -->
-
 # dap305/Helsinki-finetuned-EuroParl-en-to-es
 
-This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-es](https://huggingface.co/Helsinki-NLP/opus-mt-en-es) on an unknown dataset.
-It achieves the following results on the evaluation set:
+This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-es](https://huggingface.co/Helsinki-NLP/opus-mt-en-es) on a subset of the EuroParl dataset.
+It achieves the following results on the validation set:
 - Train Loss: 0.9863
 - Validation Loss: 1.1352
-- Epoch: 2
-
-## Model description
-
-More information needed
+- BLUE: 37.083
 
 ## Intended uses & limitations
 
-More information needed
+This model has been created for learning purposes at the MIARFID Automatic Translation course. 
 
 ## Training and evaluation data
 
-More information needed
-
-## Training procedure
+This model was fine-tuned with a subset of the Europarl-v7-es-en, consisting of 50.000 sentences in English and Spanish.
+Philipp Koehn. 2005. Europarl: A Parallel Corpus for Statistical Machine Translation. In Proceedings of Machine Translation Summit X: Papers, pages 79–86, Phuket, Thailand.
 
 ### Training hyperparameters
 
@@ -53,4 +55,4 @@ The following hyperparameters were used during training:
 - Transformers 4.37.0
 - TensorFlow 2.13.0
 - Datasets 2.16.1
-- Tokenizers 0.15.1
+- Tokenizers 0.15.1