Instructions to use Anguuuuus/mydata-sentence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anguuuuus/mydata-sentence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Anguuuuus/mydata-sentence")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Anguuuuus/mydata-sentence") model = AutoModelForAudioClassification.from_pretrained("Anguuuuus/mydata-sentence", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- README.md +18 -18
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
CHANGED
|
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 17 |
|
| 18 |
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
|
| 19 |
It achieves the following results on the evaluation set:
|
| 20 |
-
- Loss: 0.
|
| 21 |
-
- Accuracy: 0.
|
| 22 |
|
| 23 |
## Model description
|
| 24 |
|
|
@@ -37,7 +37,7 @@ More information needed
|
|
| 37 |
### Training hyperparameters
|
| 38 |
|
| 39 |
The following hyperparameters were used during training:
|
| 40 |
-
- learning_rate:
|
| 41 |
- train_batch_size: 8
|
| 42 |
- eval_batch_size: 8
|
| 43 |
- seed: 42
|
|
@@ -50,21 +50,21 @@ The following hyperparameters were used during training:
|
|
| 50 |
|
| 51 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 52 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 53 |
-
| 0.
|
| 54 |
-
| 0.
|
| 55 |
-
| 0.
|
| 56 |
-
| 0.
|
| 57 |
-
| 0.
|
| 58 |
-
| 0.
|
| 59 |
-
| 0.
|
| 60 |
-
| 0.
|
| 61 |
-
| 0.
|
| 62 |
-
| 0.
|
| 63 |
-
| 0.
|
| 64 |
-
| 0.
|
| 65 |
-
| 0.
|
| 66 |
-
| 0.
|
| 67 |
-
| 0.
|
| 68 |
|
| 69 |
|
| 70 |
### Framework versions
|
|
|
|
| 17 |
|
| 18 |
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
|
| 19 |
It achieves the following results on the evaluation set:
|
| 20 |
+
- Loss: 0.5921
|
| 21 |
+
- Accuracy: 0.8462
|
| 22 |
|
| 23 |
## Model description
|
| 24 |
|
|
|
|
| 37 |
### Training hyperparameters
|
| 38 |
|
| 39 |
The following hyperparameters were used during training:
|
| 40 |
+
- learning_rate: 0.0001
|
| 41 |
- train_batch_size: 8
|
| 42 |
- eval_batch_size: 8
|
| 43 |
- seed: 42
|
|
|
|
| 50 |
|
| 51 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 52 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 53 |
+
| 0.7353 | 1.0 | 7 | 0.7616 | 0.4615 |
|
| 54 |
+
| 0.6483 | 2.0 | 14 | 0.7718 | 0.3846 |
|
| 55 |
+
| 0.6112 | 3.0 | 21 | 0.9766 | 0.3846 |
|
| 56 |
+
| 0.6374 | 4.0 | 28 | 0.9559 | 0.3846 |
|
| 57 |
+
| 0.8214 | 5.0 | 35 | 0.9544 | 0.3846 |
|
| 58 |
+
| 0.6503 | 6.0 | 42 | 0.7424 | 0.3846 |
|
| 59 |
+
| 0.7003 | 7.0 | 49 | 0.7507 | 0.3846 |
|
| 60 |
+
| 0.7017 | 8.0 | 56 | 0.7447 | 0.3846 |
|
| 61 |
+
| 0.5717 | 9.0 | 63 | 0.7188 | 0.3846 |
|
| 62 |
+
| 0.616 | 10.0 | 70 | 0.7253 | 0.3846 |
|
| 63 |
+
| 0.6304 | 11.0 | 77 | 0.7149 | 0.3846 |
|
| 64 |
+
| 0.5068 | 12.0 | 84 | 0.6676 | 0.5385 |
|
| 65 |
+
| 0.5476 | 13.0 | 91 | 0.6324 | 0.8462 |
|
| 66 |
+
| 0.4521 | 14.0 | 98 | 0.5971 | 0.8462 |
|
| 67 |
+
| 0.4567 | 15.0 | 105 | 0.5921 | 0.8462 |
|
| 68 |
|
| 69 |
|
| 70 |
### Framework versions
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 378302360
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0991ae8abdb84c1fa6b4db7faa8707699928e034416c3e6e931ebf84a015895c
|
| 3 |
size 378302360
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4664
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:34e3192b3b6b8dff867dd5ed8c56e6b599651be6dac4dc1ad36afde966ce929c
|
| 3 |
size 4664
|