metadata
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: acer_nitro_mdberta
results: []
acer_nitro_mdberta
This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7384
- F1: 0.7593
- Roc Auc: 0.8588
- Accuracy: 0.6506
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 166 | 0.5907 | 0.7281 | 0.8497 | 0.5904 |
| No log | 2.0 | 332 | 0.5260 | 0.6836 | 0.8576 | 0.5181 |
| No log | 3.0 | 498 | 0.7023 | 0.7324 | 0.8381 | 0.6024 |
| 0.3153 | 4.0 | 664 | 0.7848 | 0.7245 | 0.8168 | 0.5904 |
| 0.3153 | 5.0 | 830 | 0.6979 | 0.7436 | 0.8666 | 0.5904 |
| 0.3153 | 6.0 | 996 | 0.8550 | 0.7426 | 0.8337 | 0.6265 |
| 0.1464 | 7.0 | 1162 | 0.7102 | 0.7830 | 0.8700 | 0.6747 |
| 0.1464 | 8.0 | 1328 | 0.7172 | 0.7721 | 0.8662 | 0.6627 |
| 0.1464 | 9.0 | 1494 | 0.7812 | 0.7664 | 0.8613 | 0.6506 |
| 0.0781 | 10.0 | 1660 | 0.7384 | 0.7593 | 0.8588 | 0.6506 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0