arpagon commited on
Commit
3ec1ee6
1 Parent(s): 0fa3e08

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +9 -6
README.md CHANGED
@@ -1,20 +1,23 @@
1
  ---
 
 
2
  license: apache-2.0
3
  tags:
 
4
  - generated_from_trainer
5
  datasets:
6
- - common_voice_11_0
7
  metrics:
8
  - wer
9
  model-index:
10
- - name: openai/whisper-large-v2
11
  results:
12
  - task:
13
  name: Automatic Speech Recognition
14
  type: automatic-speech-recognition
15
  dataset:
16
- name: common_voice_11_0
17
- type: common_voice_11_0
18
  config: es
19
  split: test
20
  args: es
@@ -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
- # openai/whisper-large-v2
31
 
32
- This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_11_0 dataset.
33
  It achieves the following results on the evaluation set:
34
  - Loss: 0.1702
35
  - Wer: 5.2882
 
1
  ---
2
+ language:
3
+ - es
4
  license: apache-2.0
5
  tags:
6
+ - whisper-event
7
  - generated_from_trainer
8
  datasets:
9
+ - mozilla-foundation/common_voice_11_0
10
  metrics:
11
  - wer
12
  model-index:
13
+ - name: Whisper Large v2 Spanish
14
  results:
15
  - task:
16
  name: Automatic Speech Recognition
17
  type: automatic-speech-recognition
18
  dataset:
19
+ name: mozilla-foundation/common_voice_11_0 es
20
+ type: mozilla-foundation/common_voice_11_0
21
  config: es
22
  split: test
23
  args: es
 
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 Large v2 Spanish
34
 
35
+ This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 es dataset.
36
  It achieves the following results on the evaluation set:
37
  - Loss: 0.1702
38
  - Wer: 5.2882