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---
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: wav2vec2-base-random-stop-classification-2
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. -->
# wav2vec2-base-random-stop-classification-2
This model is a fine-tuned version of [](https://huggingface.co/) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4265
- Accuracy: 0.8569
## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6925 | 0.99 | 18 | 0.6506 | 0.6049 |
| 0.6667 | 1.97 | 36 | 0.6474 | 0.6396 |
| 0.5762 | 2.96 | 54 | 0.5791 | 0.7670 |
| 0.559 | 4.0 | 73 | 0.4603 | 0.7963 |
| 0.4892 | 4.99 | 91 | 0.4248 | 0.8161 |
| 0.4853 | 5.97 | 109 | 0.4544 | 0.8113 |
| 0.4452 | 6.96 | 127 | 0.5181 | 0.8011 |
| 0.4747 | 8.0 | 146 | 0.3739 | 0.8454 |
| 0.4026 | 8.99 | 164 | 0.4483 | 0.8249 |
| 0.4326 | 9.97 | 182 | 0.3992 | 0.8447 |
| 0.4149 | 10.96 | 200 | 0.3607 | 0.8542 |
| 0.3995 | 12.0 | 219 | 0.4662 | 0.8256 |
| 0.36 | 12.99 | 237 | 0.4375 | 0.8495 |
| 0.3807 | 13.97 | 255 | 0.4013 | 0.8351 |
| 0.401 | 14.96 | 273 | 0.4875 | 0.8311 |
| 0.3349 | 16.0 | 292 | 0.3810 | 0.8610 |
| 0.3279 | 16.99 | 310 | 0.4288 | 0.8392 |
| 0.3111 | 17.97 | 328 | 0.4160 | 0.8460 |
| 0.3092 | 18.96 | 346 | 0.4469 | 0.8379 |
| 0.3202 | 20.0 | 365 | 0.4294 | 0.8563 |
| 0.3027 | 20.99 | 383 | 0.3928 | 0.8569 |
| 0.3022 | 21.97 | 401 | 0.4829 | 0.8399 |
| 0.2934 | 22.96 | 419 | 0.3978 | 0.8604 |
| 0.2789 | 24.0 | 438 | 0.4027 | 0.8610 |
| 0.2714 | 24.66 | 450 | 0.4265 | 0.8569 |
### Framework versions
- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2
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