update model card README.md

README.md

@@ -1,41 +1,38 @@
 ---
-language:
-- zh
 license: apache-2.0
 tags:
-- whisper-event
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_11_0
+- common_voice_11_0
 metrics:
 - wer
 model-index:
-- name: Whisper Small Traditional Chinese
+- name: kimbochen/whisper-small-zh-tw
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: mozilla-foundation/common_voice_11_0 zh-TW
-      type: mozilla-foundation/common_voice_11_0
+      name: common_voice_11_0
+      type: common_voice_11_0
       config: zh-TW
       split: test
       args: zh-TW
     metrics:
     - name: Wer
       type: wer
-      value: 32.594792142530835
+      value: 32.04202832343535
 ---
 
 <!-- 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 Traditional Chinese
+# kimbochen/whisper-small-zh-tw
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 zh-TW dataset.
+This model is a fine-tuned version of [kimbochen/whisper-small-zh-tw](https://huggingface.co/kimbochen/whisper-small-zh-tw) on the common_voice_11_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3250
-- Wer: 32.5948
+- Loss: 0.4334
+- Wer: 32.0420
 
 ## Model description
 
@@ -60,19 +57,19 @@ 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: 800
-- training_steps: 1000
+- lr_scheduler_warmup_steps: 1200
+- training_steps: 2000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer     |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.3465        | 1.05  | 200  | 0.3499          | 41.9324 |
-| 0.2137        | 2.1   | 400  | 0.2953          | 36.2951 |
-| 0.1255        | 4.01  | 600  | 0.2927          | 33.7232 |
-| 0.0509        | 5.06  | 800  | 0.3149          | 34.0566 |
-| 0.0164        | 6.11  | 1000 | 0.3250          | 32.5948 |
+| 0.0066        | 2.05  | 400  | 0.3743          | 32.9100 |
+| 0.0084        | 5.03  | 800  | 0.3787          | 33.4171 |
+| 0.0098        | 8.01  | 1200 | 0.3979          | 33.2481 |
+| 0.0019        | 10.06 | 1600 | 0.4084          | 32.3116 |
+| 0.0008        | 13.04 | 2000 | 0.4334          | 32.0420 |
 
 
 ### Framework versions