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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trim-lesson7-classification
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. -->
# trim-lesson7-classification
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1884
- Accuracy: 0.9670
- F1-score: 0.9671
- Recall-score: 0.9670
- Precision-score: 0.9679
## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Recall-score | Precision-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------------:|:---------------:|
| 3.8363 | 1.0 | 223 | 3.7557 | 0.1494 | 0.0778 | 0.1494 | 0.0756 |
| 2.7979 | 2.0 | 446 | 2.5827 | 0.6355 | 0.5759 | 0.6355 | 0.6166 |
| 1.6429 | 3.0 | 669 | 1.5768 | 0.9235 | 0.9229 | 0.9235 | 0.9280 |
| 1.659 | 4.0 | 892 | 0.8894 | 0.9440 | 0.9439 | 0.9440 | 0.9461 |
| 0.5305 | 5.0 | 1115 | 0.5156 | 0.9557 | 0.9557 | 0.9557 | 0.9573 |
| 0.3831 | 6.0 | 1338 | 0.3869 | 0.9537 | 0.9539 | 0.9537 | 0.9560 |
| 0.1822 | 7.0 | 1561 | 0.3246 | 0.9576 | 0.9576 | 0.9576 | 0.9589 |
| 0.1308 | 8.0 | 1784 | 0.2840 | 0.9523 | 0.9524 | 0.9523 | 0.9540 |
| 0.1087 | 9.0 | 2007 | 0.3299 | 0.9401 | 0.9393 | 0.9401 | 0.9460 |
| 0.0968 | 10.0 | 2230 | 0.2539 | 0.9548 | 0.9549 | 0.9548 | 0.9571 |
| 0.1088 | 11.0 | 2453 | 0.2290 | 0.9606 | 0.9606 | 0.9606 | 0.9617 |
| 0.7219 | 12.0 | 2676 | 0.2346 | 0.9606 | 0.9607 | 0.9606 | 0.9616 |
| 0.2103 | 13.0 | 2899 | 0.2119 | 0.9629 | 0.9629 | 0.9629 | 0.9640 |
| 0.0414 | 14.0 | 3122 | 0.2431 | 0.9590 | 0.9590 | 0.9590 | 0.9603 |
| 0.9212 | 15.0 | 3345 | 0.2141 | 0.9651 | 0.9651 | 0.9651 | 0.9664 |
| 0.0244 | 16.0 | 3568 | 0.2185 | 0.9620 | 0.9620 | 0.9620 | 0.9633 |
| 0.0468 | 17.0 | 3791 | 0.1949 | 0.9645 | 0.9645 | 0.9645 | 0.9655 |
| 1.2045 | 18.0 | 4014 | 0.1985 | 0.9637 | 0.9637 | 0.9637 | 0.9648 |
| 0.1907 | 19.0 | 4237 | 0.1894 | 0.9634 | 0.9635 | 0.9634 | 0.9646 |
| 0.0185 | 20.0 | 4460 | 0.1956 | 0.9640 | 0.9640 | 0.9640 | 0.9648 |
| 0.0159 | 21.0 | 4683 | 0.2118 | 0.9601 | 0.9601 | 0.9601 | 0.9610 |
| 0.0633 | 22.0 | 4906 | 0.1953 | 0.9634 | 0.9635 | 0.9634 | 0.9646 |
| 0.0244 | 23.0 | 5129 | 0.1915 | 0.9665 | 0.9665 | 0.9665 | 0.9673 |
| 0.008 | 24.0 | 5352 | 0.1842 | 0.9690 | 0.9690 | 0.9690 | 0.9698 |
| 0.2523 | 25.0 | 5575 | 0.1884 | 0.9670 | 0.9671 | 0.9670 | 0.9679 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.3.0+cu118
- Datasets 3.0.1
- Tokenizers 0.20.0
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