update model card README.md

README.md

@@ -2,47 +2,30 @@
 language:
 - af
 license: apache-2.0
-task:
-- automatic-speech-recognition
 tags:
 - whisper-event
 - generated_from_trainer
-- hf-asr-leaderboard
 datasets:
 - google/fleurs
-- OpenSLR/SLR32
 model-index:
-- name: whisper-base-af-za-V3.1-Ari
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: google/fleurs
-      type: google/fleurs
-      config: af_za
-      split: test
-      args: af_za
-    metrics:
-    - name: Wer
-      type: wer
-      value: 31.3287
+- name: whisper-base-af-za-V4-Ari
+  results: []
 ---
 
 <!-- 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. -->
 
-# whisper-base-af-za -V3.1- Ari
+# whisper-base-af-za-V4-Ari
 
-This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the FLEURS+OpenSLR32 dataset.
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Google FLEURS dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.9495
-- eval_wer: 31.3287
-- eval_runtime: 140.1696
-- eval_samples_per_second: 6.692
-- eval_steps_per_second: 0.421
-- epoch: 28.41
-- step: 2500
+- eval_loss: 1.0084
+- eval_wer: 32.0267
+- eval_runtime: 152.7461
+- eval_samples_per_second: 6.154
+- eval_steps_per_second: 0.386
+- epoch: 51.14
+- step: 4500
 
 ## Model description
 
@@ -75,5 +58,5 @@ The following hyperparameters were used during training:
 
 - Transformers 4.26.0.dev0
 - Pytorch 1.13.0+cu116
-- Datasets 2.7.1.dev0
+- Datasets 2.8.1.dev0
 - Tokenizers 0.13.2