Update README.md

README.md

@@ -8,6 +8,8 @@ tags:
 base_model: openai/whisper-medium
 datasets:
 - mozilla-foundation/common_voice_17_0
+- google/fleurs
+- facebook/multilingual_librispeech
 metrics:
 - wer
 model-index:
@@ -50,6 +52,7 @@ model-index:
     - type: wer
       value: 13.57
       name: WER
+pipeline_tag: automatic-speech-recognition
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -57,7 +60,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Whisper Medium Mixed-Portuguese
 
-This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_17_0 pt dataset.
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the pt datasets:
+- mozilla-foundation/common_voice_17_0
+- google/fleurs
+- facebook/multilingual_librispeech
+
 It achieves the following results on the evaluation set:
 - Loss: 0.1353
 - Wer: 7.1230
@@ -105,4 +112,4 @@ The following hyperparameters were used during training:
 - Transformers 4.42.0.dev0
 - Pytorch 2.3.0+cu121
 - Datasets 2.19.1
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1