Instructions to use deepthink8/Deeepfake-audio-Recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepthink8/Deeepfake-audio-Recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="deepthink8/Deeepfake-audio-Recognition")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("deepthink8/Deeepfake-audio-Recognition") model = AutoModelForAudioClassification.from_pretrained("deepthink8/Deeepfake-audio-Recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
README.md
CHANGED
|
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 18 |
|
| 19 |
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
|
| 20 |
It achieves the following results on the evaluation set:
|
| 21 |
-
- Loss: 0.
|
| 22 |
-
- Accuracy: 0.
|
| 23 |
|
| 24 |
## Model description
|
| 25 |
|
|
@@ -53,7 +53,7 @@ The following hyperparameters were used during training:
|
|
| 53 |
|
| 54 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 55 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 56 |
-
| 0.
|
| 57 |
|
| 58 |
|
| 59 |
### Framework versions
|
|
|
|
| 18 |
|
| 19 |
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
|
| 20 |
It achieves the following results on the evaluation set:
|
| 21 |
+
- Loss: 0.6931
|
| 22 |
+
- Accuracy: 0.5053
|
| 23 |
|
| 24 |
## Model description
|
| 25 |
|
|
|
|
| 53 |
|
| 54 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 55 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 56 |
+
| 0.694 | 1.0 | 496 | 0.6931 | 0.5053 |
|
| 57 |
|
| 58 |
|
| 59 |
### Framework versions
|