update model card README.md

README.md

@@ -1,41 +1,38 @@
 ---
-language:
-- ja
 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 Base Japanese
+- name: whisper-base-ja-cv11
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: mozilla-foundation/common_voice_11_0 ja
-      type: mozilla-foundation/common_voice_11_0
+      name: common_voice_11_0
+      type: common_voice_11_0
       config: ja
       split: test
       args: ja
     metrics:
     - name: Wer
       type: wer
-      value: 22.51334731203637
+      value: 21.991788980318223
 ---
 
 <!-- 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 Base Japanese
+# whisper-base-ja-cv11
 
-This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_11_0 ja dataset.
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_voice_11_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4601
-- Wer: 22.5133
+- Loss: 0.6532
+- Wer: 21.9918
 
 ## Model description
 
@@ -55,25 +52,34 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 16
-- eval_batch_size: 8
+- train_batch_size: 32
+- eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: constant_with_warmup
-- lr_scheduler_warmup_steps: 50
-- training_steps: 1000
+- lr_scheduler_warmup_steps: 500
+- training_steps: 10000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.5019        | 1.0   | 1000 | 0.4601          | 22.5133 |
+| Training Loss | Epoch | Step  | Validation Loss | Wer     |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|
+| 0.3273        | 3.02  | 1000  | 0.4225          | 20.8253 |
+| 0.0923        | 7.0   | 2000  | 0.4643          | 21.2200 |
+| 0.0164        | 10.02 | 3000  | 0.5403          | 22.9627 |
+| 0.006         | 14.01 | 4000  | 0.5820          | 21.0861 |
+| 0.0046        | 17.02 | 5000  | 0.5852          | 22.0728 |
+| 0.0034        | 21.01 | 6000  | 0.6113          | 21.6623 |
+| 0.0028        | 24.03 | 7000  | 0.6582          | 22.3266 |
+| 0.0025        | 28.01 | 8000  | 0.6350          | 22.2332 |
+| 0.0029        | 32.0  | 9000  | 0.6468          | 22.1098 |
+| 0.0014        | 35.02 | 10000 | 0.6532          | 21.9918 |
 
 
 ### Framework versions
 
 - Transformers 4.26.0.dev0
-- Pytorch 1.13.0+cu117
+- Pytorch 1.13.1+cu117
 - Datasets 2.8.1.dev0
 - Tokenizers 0.13.2