update model card README.md

README.md

@@ -6,7 +6,7 @@ tags:
 - hf-asr-leaderboard
 - generated_from_trainer
 datasets:
-- google/fleurs
+- Bingsu/zeroth-korean
 metrics:
 - wer
 model-index:
@@ -16,15 +16,15 @@ model-index:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: Google Fleures
-      type: google/fleurs
-      config: clean
+      name: Zeroth-Korean
+      type: Bingsu/zeroth-korean
+      config: null
       split: None
       args: 'config:ko, split: test'
     metrics:
     - name: Wer
       type: wer
-      value: 174.6096
+      value: 59.524168046980876
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,10 +32,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Whisper Tiny Ko - TJ
 
-This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Google Fleures dataset.
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Zeroth-Korean dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.789679
-- Wer: 174.6096
+- Loss: 2.6946
+- Wer: 59.5242
 
 ## Model description
 
@@ -60,22 +60,15 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
-- training_steps: 8000
+- lr_scheduler_warmup_steps: 1
+- training_steps: 1
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer      |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.1157        | 6.29  | 1000 | 0.5599          | 58.7828  |
-| 0.0174        | 12.58 | 2000 | 0.6095          | 143.0979 |
-| 0.0072        | 18.87 | 3000 | 0.6457          | 214.4074 |
-| 0.005         | 25.16 | 4000 | 0.6558          | 233.4280 |
-| 0.001500      | 32.16 | 5000 | 0.735888        | 148.2789 |
-| 0.000600      | 38.16 | 6000 | 0.764227        | 153.5841 |
-| 0.000400      | 44.16 | 7000 | 0.782319        | 174.4144 |
-| 0.000400      | 52.16 | 8000 | 0.789679        | 174.6096 |
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 2.6768        | 0.0   | 1    | 2.6946          | 59.5242 |
 
 
 ### Framework versions