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estudiante_MC318_profesor_MViT_akl_VIOPERU
DanJoshua/estudiante_MC318_profesor_MViT_akl_VIOPERU
estudiante_MC318_profesor_MViT_akl_VIOPERU is a machine learning model from DanJoshua. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Access
- Public
- Created
- Nov 5, 2024
- Updated
- Nov 5, 2024
- SHA
- 6e4b2cca
Model card
From the Hugging Face model README
<!-- 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. -->
estudiante_MC318_profesor_MViT_akl_VIOPERU
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6486
- Accuracy: 0.6696
- F1: 0.6636
- Precision: 0.6828
- Recall: 0.6696
- Roc Auc: 0.7280
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: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 21
- training_steps: 210
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc |
|---|---|---|---|---|---|---|---|---|
| 3.1309 | 1.0095 | 10 | 0.6797 | 0.5536 | 0.4805 | 0.6224 | 0.5536 | 0.6633 |
| 2.7485 | 2.0190 | 20 | 0.6672 | 0.5357 | 0.4944 | 0.5530 | 0.5357 | 0.6747 |
| 2.7139 | 3.0286 | 30 | 0.6622 | 0.6429 | 0.6410 | 0.6458 | 0.6429 | 0.6709 |
| 2.5183 | 4.0381 | 40 | 0.6592 | 0.6607 | 0.6597 | 0.6626 | 0.6607 | 0.6747 |
| 2.3888 | 6.0095 | 50 | 0.6528 | 0.6786 | 0.6782 | 0.6795 | 0.6786 | 0.6760 |
| 2.2645 | 7.0190 | 60 | 0.6537 | 0.6786 | 0.6748 | 0.6872 | 0.6786 | 0.6722 |
| 2.1218 | 8.0286 | 70 | 0.6496 | 0.6786 | 0.6748 | 0.6872 | 0.6786 | 0.6735 |
| 1.8439 | 9.0381 | 80 | 0.6484 | 0.6607 | 0.6580 | 0.6660 | 0.6607 | 0.6607 |
| 1.8092 | 11.0095 | 90 | 0.6502 | 0.6607 | 0.6553 | 0.6714 | 0.6607 | 0.6518 |
| 1.667 | 12.0190 | 100 | 0.6523 | 0.6607 | 0.6580 | 0.6660 | 0.6607 | 0.6582 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.0.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.2
- Library
- transformers
- Created
- Nov 5, 2024
- Updated
- Nov 5, 2024