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 Small Japanese Elite
+- name: whisper-small-ja-elite
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: Elite35P-Server/EliteVoiceProject twitter
-      type: Elite35P-Server/EliteVoiceProject
-      config: twitter
+      name: elite_voice_project
+      type: elite_voice_project
+      config: twitch
       split: test
-      args: twitter
+      args: twitch
     metrics:
     - name: Wer
       type: wer
-      value: 4.878048780487805
+      value: 23.296888141295206
 ---
 
 <!-- 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 Japanese Elite
+# whisper-small-ja-elite
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Elite35P-Server/EliteVoiceProject twitter dataset.
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the elite_voice_project dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1502
-- Wer: 4.8780
+- Loss: 0.9180
+- Wer: 23.2969
 
 ## Model description
 
@@ -60,19 +57,24 @@ The following hyperparameters were used during training:
 - 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: 5000
+- lr_scheduler_warmup_steps: 100
+- training_steps: 10000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer    |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.0004        | 58.0  | 1000 | 0.1129          | 1.8293 |
-| 0.0           | 117.0 | 2000 | 0.1232          | 1.8293 |
-| 0.0           | 176.0 | 3000 | 0.1327          | 1.8293 |
-| 0.0           | 235.0 | 4000 | 0.1401          | 4.8780 |
-| 0.0           | 294.0 | 5000 | 0.1502          | 4.8780 |
+| Training Loss | Epoch | Step  | Validation Loss | Wer     |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|
+| 0.0033        | 18.0  | 1000  | 0.6728          | 25.3154 |
+| 0.008         | 37.0  | 2000  | 0.6984          | 23.3810 |
+| 0.0002        | 56.0  | 3000  | 0.7486          | 24.4743 |
+| 0.0001        | 75.0  | 4000  | 0.7753          | 24.4743 |
+| 0.0           | 94.0  | 5000  | 0.8014          | 24.0538 |
+| 0.0           | 113.0 | 6000  | 0.8244          | 24.3902 |
+| 0.0           | 132.0 | 7000  | 0.8468          | 23.8015 |
+| 0.0           | 150.0 | 8000  | 0.8699          | 23.4651 |
+| 0.0           | 169.0 | 9000  | 0.8936          | 23.2128 |
+| 0.0           | 188.0 | 10000 | 0.9180          | 23.2969 |
 
 
 ### Framework versions