metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: group2_non_all_zero
results: []
group2_non_all_zero
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3907
- Precision: 0.0415
- Recall: 0.086
- F1: 0.0560
- Accuracy: 0.9044
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 172 | 0.2512 | 0.0608 | 0.044 | 0.0510 | 0.9439 |
| No log | 2.0 | 344 | 0.2667 | 0.0355 | 0.048 | 0.0408 | 0.9194 |
| 0.4561 | 3.0 | 516 | 0.2883 | 0.0445 | 0.078 | 0.0566 | 0.9198 |
| 0.4561 | 4.0 | 688 | 0.3610 | 0.0379 | 0.092 | 0.0537 | 0.8968 |
| 0.4561 | 5.0 | 860 | 0.3840 | 0.0528 | 0.094 | 0.0676 | 0.9095 |
| 0.1508 | 6.0 | 1032 | 0.3907 | 0.0415 | 0.086 | 0.0560 | 0.9044 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.13.3