noflm commited on
Commit
fd5b912
1 Parent(s): 6cb3cc3

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +10 -7
README.md CHANGED
@@ -1,20 +1,23 @@
1
  ---
2
- license: apache-2.0
 
 
3
  tags:
 
4
  - generated_from_trainer
5
  datasets:
6
- - elite_voice_project
7
  metrics:
8
  - wer
9
  model-index:
10
- - name: whisper-base-ja-elite
11
  results:
12
  - task:
13
  name: Automatic Speech Recognition
14
  type: automatic-speech-recognition
15
  dataset:
16
- name: elite_voice_project
17
- type: elite_voice_project
18
  config: twitter
19
  split: test
20
  args: twitter
@@ -27,9 +30,9 @@ model-index:
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
28
  should probably proofread and complete it, then remove this comment. -->
29
 
30
- # whisper-base-ja-elite
31
 
32
- This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the elite_voice_project dataset.
33
  It achieves the following results on the evaluation set:
34
  - Loss: 0.4385
35
  - Wer: 17.0732
 
1
  ---
2
+ language:
3
+ - ja
4
+ license: other
5
  tags:
6
+ - whisper-event
7
  - generated_from_trainer
8
  datasets:
9
+ - Elite35P-Server/EliteVoiceProject
10
  metrics:
11
  - wer
12
  model-index:
13
+ - name: Whisper Base Japanese Elite
14
  results:
15
  - task:
16
  name: Automatic Speech Recognition
17
  type: automatic-speech-recognition
18
  dataset:
19
+ name: Elite35P-Server/EliteVoiceProject twitter
20
+ type: Elite35P-Server/EliteVoiceProject
21
  config: twitter
22
  split: test
23
  args: twitter
 
30
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
31
  should probably proofread and complete it, then remove this comment. -->
32
 
33
+ # Whisper Base Japanese Elite
34
 
35
+ This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Elite35P-Server/EliteVoiceProject twitter dataset.
36
  It achieves the following results on the evaluation set:
37
  - Loss: 0.4385
38
  - Wer: 17.0732