metadata
base_model: facebook/wav2vec2-base-960h
library_name: transformers
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-960h-EMOPIA
results: []
wav2vec2-base-960h-EMOPIA
This model is a fine-tuned version of facebook/wav2vec2-base-960h on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4624
- Accuracy: 0.6620
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2041 | 1.0 | 807 | 1.1999 | 0.3662 |
| 1.067 | 2.0 | 1614 | 1.4613 | 0.4507 |
| 1.1007 | 3.0 | 2421 | 1.5213 | 0.4085 |
| 1.1945 | 4.0 | 3228 | 1.6642 | 0.6056 |
| 1.3665 | 5.0 | 4035 | 2.9908 | 0.4366 |
| 1.4506 | 6.0 | 4842 | 1.9230 | 0.6056 |
| 1.495 | 7.0 | 5649 | 1.6813 | 0.6761 |
| 1.2605 | 8.0 | 6456 | 1.8937 | 0.6620 |
| 1.2713 | 9.0 | 7263 | 1.6284 | 0.6901 |
| 1.2608 | 10.0 | 8070 | 1.9438 | 0.6479 |
| 1.2068 | 11.0 | 8877 | 1.5237 | 0.7183 |
| 1.0478 | 12.0 | 9684 | 2.0007 | 0.6338 |
| 1.1282 | 13.0 | 10491 | 1.5307 | 0.7465 |
| 0.9433 | 14.0 | 11298 | 2.0042 | 0.6479 |
| 0.9574 | 15.0 | 12105 | 2.1985 | 0.6338 |
| 0.8737 | 16.0 | 12912 | 2.1568 | 0.6479 |
| 0.8937 | 17.0 | 13719 | 2.2980 | 0.6197 |
| 0.8681 | 18.0 | 14526 | 2.3268 | 0.6197 |
| 0.8005 | 19.0 | 15333 | 2.4827 | 0.6479 |
| 0.8176 | 20.0 | 16140 | 2.4842 | 0.6338 |
| 0.8133 | 21.0 | 16947 | 2.0620 | 0.6761 |
| 0.7404 | 22.0 | 17754 | 2.4148 | 0.6479 |
| 0.7134 | 23.0 | 18561 | 2.3389 | 0.6761 |
| 0.6573 | 24.0 | 19368 | 2.6972 | 0.6197 |
| 0.6848 | 25.0 | 20175 | 2.3375 | 0.6761 |
| 0.6161 | 26.0 | 20982 | 2.4791 | 0.6620 |
| 0.6301 | 27.0 | 21789 | 2.3807 | 0.6479 |
| 0.5758 | 28.0 | 22596 | 2.2243 | 0.6901 |
| 0.5598 | 29.0 | 23403 | 2.4130 | 0.6620 |
| 0.6066 | 30.0 | 24210 | 2.4624 | 0.6620 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1