Update README.md

README.md

@@ -2,9 +2,8 @@
 license: apache-2.0
 base_model: openai/whisper-small
 tags:
-- generated_from_trainer
-datasets:
-- common_voice_16_1
+- audio
+- automatic-speech-recognition
 metrics:
 - wer
 model-index:
@@ -23,6 +22,10 @@ model-index:
     - name: Wer
       type: wer
       value: 47.726437288634024
+language:
+- ar
+library_name: transformers
+pipeline_tag: automatic-speech-recognition
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,14 +33,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 # whisper-small-ar-v2
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_16_1 dataset.
+This model is for Arabic automatic speech recognition (ASR). It is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Arabic portion of the `mozilla-foundation/common_voice_16_1` dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.4007
 - Wer: 47.7264
 
 ## Model description
 
-More information needed
+Whisper model fine-tuned on Arabic data, following the [official tutorial](https://huggingface.co/blog/fine-tune-whisper).
 
 ## Intended uses & limitations
 
@@ -45,7 +48,8 @@ More information needed
 
 ## Training and evaluation data
 
-More information needed
+Training Data: CommonVoice (v16.1) Arabic train + validation splits  
+Validation Data: CommonVoice (v16.1) Arabic test split
 
 ## Training procedure
 
@@ -81,4 +85,4 @@ The following hyperparameters were used during training:
 - Transformers 4.38.1
 - Pytorch 2.1.0+cu118
 - Datasets 2.17.1
-- Tokenizers 0.15.2
+- Tokenizers 0.15.2