update model card README.md

README.md

@@ -1,39 +1,38 @@
 ---
 license: apache-2.0
 tags:
-- whisper-event
 - generated_from_trainer
 datasets:
-- google/fleurs
+- fleurs
 metrics:
 - wer
 model-index:
-- name: Whisper Small Pashto
+- name: openai/whisper-small
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: google/fleurs ps_af
-      type: google/fleurs
+      name: fleurs
+      type: fleurs
       config: ps_af
       split: test
       args: ps_af
     metrics:
     - name: Wer
       type: wer
-      value: 58.830205811138015
+      value: 57.99031476997578
 ---
 
 <!-- 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 Small Pashto
+# openai/whisper-small
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs ps_af dataset.
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9642
-- Wer: 58.8302
+- Loss: 1.0876
+- Wer: 57.9903
 
 ## Model description
 
@@ -59,7 +58,7 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- training_steps: 300
+- training_steps: 400
 - mixed_precision_training: Native AMP
 
 ### Training results
@@ -69,6 +68,7 @@ The following hyperparameters were used during training:
 | 2.1183        | 3.7   | 100  | 1.3170          | 76.9522 |
 | 0.8565        | 7.41  | 200  | 0.9367          | 61.9930 |
 | 0.2246        | 11.11 | 300  | 0.9642          | 58.8302 |
+| 0.054         | 14.81 | 400  | 1.0876          | 57.9903 |
 
 
 ### Framework versions