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: 89.14951573849879
+      value: 66.00332929782083
 ---
 
 <!-- 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: 1.3860
-- Wer: 89.1495
+- Loss: 1.0277
+- Wer: 66.0033
 
 ## Model description
 
@@ -60,18 +59,24 @@ The following hyperparameters were used during training:
 - 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: 10
-- training_steps: 400
+- lr_scheduler_warmup_steps: 50
+- training_steps: 1000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer      |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.9754        | 14.29 | 100  | 1.9261          | 240.8596 |
-| 1.5323        | 28.57 | 200  | 1.5718          | 168.5608 |
-| 1.338         | 42.86 | 300  | 1.4249          | 96.6480  |
-| 1.282         | 57.14 | 400  | 1.3860          | 89.1495  |
+| Training Loss | Epoch  | Step | Validation Loss | Wer      |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 2.0871        | 14.29  | 100  | 2.0102          | 230.2739 |
+| 1.465         | 28.57  | 200  | 1.4969          | 137.2427 |
+| 1.1617        | 42.86  | 300  | 1.2716          | 76.3242  |
+| 1.0019        | 57.14  | 400  | 1.1645          | 71.3756  |
+| 0.9052        | 71.43  | 500  | 1.1051          | 69.7866  |
+| 0.8334        | 85.71  | 600  | 1.0691          | 68.2657  |
+| 0.7838        | 100.0  | 700  | 1.0483          | 67.1686  |
+| 0.7539        | 114.29 | 800  | 1.0363          | 66.4195  |
+| 0.7377        | 128.57 | 900  | 1.0297          | 66.2001  |
+| 0.7325        | 142.86 | 1000 | 1.0277          | 66.0033  |
 
 
 ### Framework versions