Update README.md

README.md

@@ -7,6 +7,13 @@ metrics:
 model-index:
 - name: whisper-small-es-ja
   results: []
+datasets:
+- Marianoleiras/voxpopuli_es-ja
+language:
+- es
+- ja
+base_model:
+- openai/whisper-small
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -14,7 +21,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # whisper-small-es-ja
 
-This model was trained from scratch on an unknown dataset.
+This model is a fine-tuned version of OpenAI's whisper-small on the Marianoleiras/voxpopuli_es-ja dataset, designed for Spanish-to-Japanese and Japanese-to-Spanish speech-to-text (STT) tasks.
+It leverages OpenAI's Whisper architecture, which is well-suited for multilingual speech recognition and translation tasks.
+The model achieves robust performance on both the evaluation and test sets, demonstrating its effectiveness in multilingual STT applications.
+
 It achieves the following results on the evaluation set:
 - Loss: 1.1724
 - Bleu: 22.2850
@@ -22,18 +32,6 @@ It achieves the following results on the evaluation set:
 It achieves the following results on the test set:
 - Bleu: 21.4557
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
 ## Training procedure
 
 ### Training hyperparameters
@@ -74,4 +72,4 @@ The following hyperparameters were used during training:
 - Transformers 4.47.1
 - Pytorch 2.4.0+cu124
 - Datasets 3.2.0
-- Tokenizers 0.21.0
+- Tokenizers 0.21.0