|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: IDAT_aug_red_696_Wav2Vec |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# IDAT_aug_red_696_Wav2Vec |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5564 |
|
- Accuracy: 0.7667 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 3e-05 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 40 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.6862 | 0.97 | 17 | 0.6526 | 0.675 | |
|
| 0.609 | 2.0 | 35 | 0.6533 | 0.6917 | |
|
| 0.5659 | 2.97 | 52 | 0.7129 | 0.6583 | |
|
| 0.6223 | 4.0 | 70 | 0.5106 | 0.7833 | |
|
| 0.5163 | 4.97 | 87 | 0.7914 | 0.7 | |
|
| 0.6306 | 6.0 | 105 | 0.5960 | 0.75 | |
|
| 0.5651 | 6.97 | 122 | 0.7364 | 0.5583 | |
|
| 0.7081 | 8.0 | 140 | 0.7070 | 0.5 | |
|
| 0.699 | 8.97 | 157 | 0.6951 | 0.5 | |
|
| 0.6958 | 10.0 | 175 | 0.6934 | 0.5 | |
|
| 0.6978 | 10.97 | 192 | 0.6916 | 0.5 | |
|
| 0.6786 | 12.0 | 210 | 0.6940 | 0.5 | |
|
| 0.6981 | 12.97 | 227 | 0.6932 | 0.5 | |
|
| 0.6931 | 14.0 | 245 | 0.6933 | 0.5 | |
|
| 0.6939 | 14.97 | 262 | 0.6931 | 0.5 | |
|
| 0.6935 | 16.0 | 280 | 0.6931 | 0.5 | |
|
| 0.6972 | 16.97 | 297 | 0.6931 | 0.5 | |
|
| 0.6935 | 18.0 | 315 | 0.6931 | 0.5 | |
|
| 0.6931 | 18.97 | 332 | 0.6951 | 0.5 | |
|
| 0.6955 | 20.0 | 350 | 0.6921 | 0.7 | |
|
| 0.6992 | 20.97 | 367 | 0.6843 | 0.5 | |
|
| 0.6785 | 22.0 | 385 | 0.6919 | 0.5 | |
|
| 0.6661 | 22.97 | 402 | 0.6317 | 0.6417 | |
|
| 0.597 | 24.0 | 420 | 0.5620 | 0.75 | |
|
| 0.5849 | 24.97 | 437 | 0.6103 | 0.75 | |
|
| 0.5955 | 26.0 | 455 | 0.6245 | 0.725 | |
|
| 0.4777 | 26.97 | 472 | 0.5215 | 0.7833 | |
|
| 0.4726 | 28.0 | 490 | 0.5657 | 0.775 | |
|
| 0.4487 | 28.97 | 507 | 0.5306 | 0.7833 | |
|
| 0.4478 | 30.0 | 525 | 0.6591 | 0.7333 | |
|
| 0.5039 | 30.97 | 542 | 0.5304 | 0.7833 | |
|
| 0.5173 | 32.0 | 560 | 0.7111 | 0.7 | |
|
| 0.5266 | 32.97 | 577 | 0.5587 | 0.7667 | |
|
| 0.4677 | 34.0 | 595 | 0.5515 | 0.7667 | |
|
| 0.4775 | 34.97 | 612 | 0.5116 | 0.7917 | |
|
| 0.4651 | 36.0 | 630 | 0.5450 | 0.7667 | |
|
| 0.4738 | 36.97 | 647 | 0.5371 | 0.7833 | |
|
| 0.4862 | 38.0 | 665 | 0.5497 | 0.7667 | |
|
| 0.4695 | 38.86 | 680 | 0.5564 | 0.7667 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.32.1 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.13.3 |
|
|
