update model card README.md

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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.run_speech_recognition_seq2seq_streaming.py.swp

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-version https://git-lfs.github.com/spec/v1
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-size 20480

README.md

@@ -1,20 +1,21 @@
 ---
 license: apache-2.0
 tags:
+- whisper-event
 - generated_from_trainer
 datasets:
-- fleurs
+- google/fleurs
 metrics:
 - wer
 model-index:
-- name: openai/whisper-small
+- name: Whisper Small Pashto
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: fleurs
-      type: fleurs
+      name: google/fleurs ps_af
+      type: google/fleurs
       config: ps_af
       split: test
       args: ps_af
@@ -27,9 +28,9 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# openai/whisper-small
+# Whisper Small Pashto
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset.
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs ps_af dataset.
 It achieves the following results on the evaluation set:
 - Loss: 1.2309
 - Wer: 56.6510

run_speech_recognition_seq2seq_streaming.py

@@ -556,7 +556,7 @@ def main():
             elif isinstance(train_dataloader.dataset, IterableDataset):
                 train_dataloader.dataset.set_epoch(train_dataloader.dataset._epoch + 1)
 
-    model.config.dropout=0.3            
+    model.config.dropout=0.1            
 
     # Initialize Trainer
     trainer = Seq2SeqTrainer(