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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_awesome_mind_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: 0.589247311827957
---
<!-- 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. -->
# my_awesome_mind_model
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3338
- Accuracy: 0.5892
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.7071 | 0.95 | 14 | 2.7063 | 0.0602 |
| 2.7033 | 1.97 | 29 | 2.7006 | 0.0645 |
| 2.6835 | 2.98 | 44 | 2.6793 | 0.0817 |
| 2.6551 | 4.0 | 59 | 2.5549 | 0.1699 |
| 2.5023 | 4.95 | 73 | 2.3970 | 0.2258 |
| 2.4257 | 5.97 | 88 | 2.3068 | 0.2495 |
| 2.2542 | 6.98 | 103 | 2.2121 | 0.2688 |
| 2.2419 | 8.0 | 118 | 2.1736 | 0.2731 |
| 2.1278 | 8.95 | 132 | 2.1675 | 0.2430 |
| 2.0592 | 9.97 | 147 | 2.1207 | 0.2796 |
| 1.9576 | 10.98 | 162 | 2.0662 | 0.2731 |
| 1.9023 | 12.0 | 177 | 1.9738 | 0.3312 |
| 1.8367 | 12.95 | 191 | 2.0420 | 0.2903 |
| 1.7822 | 13.97 | 206 | 2.0161 | 0.2860 |
| 1.6934 | 14.98 | 221 | 2.0215 | 0.2989 |
| 1.7093 | 16.0 | 236 | 1.9287 | 0.3290 |
| 1.6158 | 16.95 | 250 | 1.8138 | 0.3849 |
| 1.5879 | 17.97 | 265 | 1.8043 | 0.3871 |
| 1.5249 | 18.98 | 280 | 1.9117 | 0.3548 |
| 1.4821 | 20.0 | 295 | 1.7242 | 0.4215 |
| 1.4629 | 20.95 | 309 | 1.6981 | 0.4538 |
| 1.3847 | 21.97 | 324 | 1.6701 | 0.4516 |
| 1.3595 | 22.98 | 339 | 1.6891 | 0.4495 |
| 1.298 | 24.0 | 354 | 1.6321 | 0.4667 |
| 1.2479 | 24.95 | 368 | 1.5519 | 0.4989 |
| 1.2135 | 25.97 | 383 | 1.5477 | 0.4839 |
| 1.1833 | 26.98 | 398 | 1.5437 | 0.5032 |
| 1.1298 | 28.0 | 413 | 1.5425 | 0.5097 |
| 1.079 | 28.95 | 427 | 1.5076 | 0.5247 |
| 1.0709 | 29.97 | 442 | 1.5288 | 0.5140 |
| 1.0286 | 30.98 | 457 | 1.4497 | 0.5419 |
| 0.9896 | 32.0 | 472 | 1.4663 | 0.5355 |
| 0.9707 | 32.95 | 486 | 1.4683 | 0.5333 |
| 0.9443 | 33.97 | 501 | 1.4977 | 0.5226 |
| 0.8998 | 34.98 | 516 | 1.4178 | 0.5505 |
| 0.9048 | 36.0 | 531 | 1.4131 | 0.5462 |
| 0.8587 | 36.95 | 545 | 1.3791 | 0.5634 |
| 0.84 | 37.97 | 560 | 1.4036 | 0.5527 |
| 0.8155 | 38.98 | 575 | 1.4139 | 0.5505 |
| 0.8086 | 40.0 | 590 | 1.3993 | 0.5462 |
| 0.808 | 40.95 | 604 | 1.3325 | 0.5914 |
| 0.7929 | 41.97 | 619 | 1.3500 | 0.5806 |
| 0.7635 | 42.98 | 634 | 1.3471 | 0.5720 |
| 0.761 | 44.0 | 649 | 1.3636 | 0.5634 |
| 0.7456 | 44.95 | 663 | 1.3551 | 0.5828 |
| 0.75 | 45.97 | 678 | 1.3431 | 0.5849 |
| 0.7232 | 46.98 | 693 | 1.3338 | 0.5871 |
| 0.7625 | 47.46 | 700 | 1.3338 | 0.5892 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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