metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_awesome_emotions_model
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6086021505376344
my_awesome_emotions_model
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.3229
- Accuracy: 0.6086
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.7077 | 0.95 | 14 | 2.7049 | 0.0645 |
| 2.7036 | 1.97 | 29 | 2.6957 | 0.0688 |
| 2.6761 | 2.98 | 44 | 2.6471 | 0.1075 |
| 2.6414 | 4.0 | 59 | 2.5442 | 0.1398 |
| 2.5034 | 4.95 | 73 | 2.3988 | 0.2774 |
| 2.4337 | 5.97 | 88 | 2.2798 | 0.3097 |
| 2.2757 | 6.98 | 103 | 2.2054 | 0.3290 |
| 2.2346 | 8.0 | 118 | 2.1204 | 0.3484 |
| 2.1167 | 8.95 | 132 | 2.0784 | 0.3484 |
| 2.0801 | 9.97 | 147 | 2.0267 | 0.3484 |
| 1.987 | 10.98 | 162 | 1.9672 | 0.3699 |
| 1.9278 | 12.0 | 177 | 1.9686 | 0.3505 |
| 1.839 | 12.95 | 191 | 1.8604 | 0.4215 |
| 1.785 | 13.97 | 206 | 1.8611 | 0.4129 |
| 1.6811 | 14.98 | 221 | 1.7791 | 0.4473 |
| 1.6858 | 16.0 | 236 | 1.7533 | 0.4323 |
| 1.562 | 16.95 | 250 | 1.7364 | 0.4473 |
| 1.5469 | 17.97 | 265 | 1.7407 | 0.4430 |
| 1.485 | 18.98 | 280 | 1.7055 | 0.4301 |
| 1.4489 | 20.0 | 295 | 1.6566 | 0.4839 |
| 1.426 | 20.95 | 309 | 1.5844 | 0.5054 |
| 1.3596 | 21.97 | 324 | 1.6252 | 0.4796 |
| 1.3212 | 22.98 | 339 | 1.5797 | 0.4860 |
| 1.248 | 24.0 | 354 | 1.5483 | 0.5097 |
| 1.1954 | 24.95 | 368 | 1.5301 | 0.5290 |
| 1.1629 | 25.97 | 383 | 1.4905 | 0.5398 |
| 1.1364 | 26.98 | 398 | 1.5040 | 0.5355 |
| 1.0897 | 28.0 | 413 | 1.5128 | 0.5484 |
| 1.0564 | 28.95 | 427 | 1.4761 | 0.5570 |
| 1.0149 | 29.97 | 442 | 1.4948 | 0.5247 |
| 0.975 | 30.98 | 457 | 1.4194 | 0.5742 |
| 0.9546 | 32.0 | 472 | 1.3986 | 0.5763 |
| 0.9235 | 32.95 | 486 | 1.4126 | 0.5634 |
| 0.8848 | 33.97 | 501 | 1.4284 | 0.5763 |
| 0.8579 | 34.98 | 516 | 1.3872 | 0.5677 |
| 0.8475 | 36.0 | 531 | 1.4108 | 0.5742 |
| 0.8018 | 36.95 | 545 | 1.3667 | 0.5849 |
| 0.7861 | 37.97 | 560 | 1.3614 | 0.5914 |
| 0.7756 | 38.98 | 575 | 1.3473 | 0.5914 |
| 0.7427 | 40.0 | 590 | 1.3346 | 0.5914 |
| 0.764 | 40.95 | 604 | 1.3229 | 0.6086 |
| 0.7283 | 41.97 | 619 | 1.3206 | 0.6 |
| 0.714 | 42.98 | 634 | 1.3266 | 0.6065 |
| 0.724 | 44.0 | 649 | 1.3377 | 0.5957 |
| 0.6928 | 44.95 | 663 | 1.3281 | 0.5978 |
| 0.7065 | 45.97 | 678 | 1.3214 | 0.6086 |
| 0.6781 | 46.98 | 693 | 1.3338 | 0.5849 |
| 0.7058 | 47.46 | 700 | 1.3330 | 0.5892 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0