noflm
commited on
Commit
•
e9e6b57
1
Parent(s):
c0564ad
update model card README.md
Browse files
README.md
CHANGED
@@ -1,20 +1,23 @@
|
|
1 |
---
|
2 |
-
|
|
|
|
|
3 |
tags:
|
|
|
4 |
- generated_from_trainer
|
5 |
datasets:
|
6 |
-
-
|
7 |
metrics:
|
8 |
- wer
|
9 |
model-index:
|
10 |
-
- name:
|
11 |
results:
|
12 |
- task:
|
13 |
name: Automatic Speech Recognition
|
14 |
type: automatic-speech-recognition
|
15 |
dataset:
|
16 |
-
name:
|
17 |
-
type:
|
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 |
-
#
|
31 |
|
32 |
-
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the
|
33 |
It achieves the following results on the evaluation set:
|
34 |
- Loss: 0.1459
|
35 |
- Wer: 11.5854
|
|
|
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: 0.1459
|
38 |
- Wer: 11.5854
|