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 Tiny Pashto
+- name: openai/whisper-base
   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: 60.05599273607748
+      value: 59.07990314769975
 ---
 
 <!-- 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 Tiny Pashto
+# openai/whisper-base
 
-This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs ps_af dataset.
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the fleurs dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8710
-- Wer: 60.0560
+- Loss: 0.9529
+- Wer: 59.0799
 
 ## Model description
 
@@ -52,14 +51,16 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-06
-- train_batch_size: 64
-- eval_batch_size: 32
+- learning_rate: 1e-07
+- train_batch_size: 32
+- eval_batch_size: 16
 - seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 30
-- training_steps: 1200
+- lr_scheduler_warmup_steps: 100
+- training_steps: 1300
 - mixed_precision_training: Native AMP
 
 ### Training results
@@ -78,6 +79,7 @@ The following hyperparameters were used during training:
 | 0.2785        | 25.0  | 1000 | 0.9339          | 59.2010 |
 | 0.2454        | 27.5  | 1100 | 0.9439          | 59.1934 |
 | 0.2297        | 30.0  | 1200 | 0.9485          | 59.0421 |
+| 0.2383        | 33.33 | 1300 | 0.9529          | 59.0799 |
 
 
 ### Framework versions