update model card README.md

README.md

@@ -1,41 +1,38 @@
 ---
-language:
-- ja
-license: other
+license: apache-2.0
 tags:
-- whisper-event
 - generated_from_trainer
 datasets:
-- Elite35P-Server/EliteVoiceProject
+- elite_voice_project
 metrics:
 - wer
 model-index:
-- name: Whisper Base Japanese Elite
+- name: whisper-base-ja-elite
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: Elite35P-Server/EliteVoiceProject twitter
-      type: Elite35P-Server/EliteVoiceProject
+      name: elite_voice_project
+      type: elite_voice_project
       config: twitter
       split: test
       args: twitter
     metrics:
     - name: Wer
       type: wer
-      value: 11.585365853658537
+      value: 17.073170731707318
 ---
 
 <!-- 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 Elite
+# whisper-base-ja-elite
 
-This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Elite35P-Server/EliteVoiceProject twitter dataset.
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the elite_voice_project dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1459
-- Wer: 11.5854
+- Loss: 0.4385
+- Wer: 17.0732
 
 ## Model description
 
@@ -55,25 +52,34 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 8
-- eval_batch_size: 4
+- train_batch_size: 32
+- eval_batch_size: 32
 - 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: 200
+- training_steps: 10000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.0009        | 29.01 | 1000 | 0.1459          | 11.5854 |
+| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
+|:-------------:|:------:|:-----:|:---------------:|:-------:|
+| 0.0002        | 111.0  | 1000  | 0.2155          | 9.7561  |
+| 0.0001        | 222.0  | 2000  | 0.2448          | 12.1951 |
+| 0.0           | 333.0  | 3000  | 0.2674          | 13.4146 |
+| 0.0           | 444.0  | 4000  | 0.2943          | 15.8537 |
+| 0.0           | 555.0  | 5000  | 0.3182          | 17.0732 |
+| 0.0           | 666.0  | 6000  | 0.3501          | 18.9024 |
+| 0.0           | 777.0  | 7000  | 0.3732          | 16.4634 |
+| 0.0           | 888.0  | 8000  | 0.4025          | 17.0732 |
+| 0.0           | 999.0  | 9000  | 0.4178          | 20.1220 |
+| 0.0           | 1111.0 | 10000 | 0.4385          | 17.0732 |
 
 
 ### 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