Update
Browse files
README.md
CHANGED
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
|
|
19 |
|
20 |
# Whisper Large V3 Turbo - Spanish
|
21 |
|
22 |
-
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 17.0 dataset.
|
23 |
|
24 |
-
The fine-tuning process reduced the Word Error Rate (WER) from
|
25 |
|
26 |
## Model description
|
27 |
|
@@ -35,8 +35,8 @@ More information needed
|
|
35 |
|
36 |
The model was trained using the Common Voice 17.0 dataset - spanish subset (mozilla-foundation/common_voice_17_0). Both the base model, whisper-large-v3-turbo, and the fine-tuned model, whisper-large-v3-turbo-es, were evaluated using Word Error Rate (WER) on the test split of the same dataset. The results are as follows:
|
37 |
|
38 |
-
- WER for whisper-large-v3-turbo (base):
|
39 |
-
- WER for whisper-large-v3-turbo-es (fine-tuned):
|
40 |
|
41 |
This significant reduction in WER shows that fine-tuning the model for spanish audio led to improved transcription accuracy compared to the original base model.
|
42 |
|
|
|
19 |
|
20 |
# Whisper Large V3 Turbo - Spanish
|
21 |
|
22 |
+
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 17.0 dataset - spanish subset.
|
23 |
|
24 |
+
The fine-tuning process reduced the Word Error Rate (WER) from 6.91% to 5.34%, demonstrating significant improvement in transcription accuracy for spanish audios.
|
25 |
|
26 |
## Model description
|
27 |
|
|
|
35 |
|
36 |
The model was trained using the Common Voice 17.0 dataset - spanish subset (mozilla-foundation/common_voice_17_0). Both the base model, whisper-large-v3-turbo, and the fine-tuned model, whisper-large-v3-turbo-es, were evaluated using Word Error Rate (WER) on the test split of the same dataset. The results are as follows:
|
37 |
|
38 |
+
- WER for whisper-large-v3-turbo (base): 6.91%
|
39 |
+
- WER for whisper-large-v3-turbo-es (fine-tuned): 5.34%
|
40 |
|
41 |
This significant reduction in WER shows that fine-tuning the model for spanish audio led to improved transcription accuracy compared to the original base model.
|
42 |
|