metadata
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-base-HSOL-WIKI-CLS
results: []
deberta-base-HSOL-WIKI-CLS
This model is a fine-tuned version of microsoft/deberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1529
- Precision: 0.7757
- Recall: 0.7782
- F1: 0.7769
- Accuracy: 0.8075
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.6211 | 1.0 | 769 | 0.7439 | 0.8403 | 0.6654 | 0.6824 | 0.7854 |
| 0.5518 | 2.0 | 1538 | 0.4591 | 0.7945 | 0.7469 | 0.7629 | 0.8114 |
| 0.4051 | 3.0 | 2307 | 0.7194 | 0.7718 | 0.7674 | 0.7695 | 0.8036 |
| 0.2264 | 4.0 | 3076 | 0.9925 | 0.7918 | 0.7546 | 0.7682 | 0.8127 |
| 0.166 | 5.0 | 3845 | 1.1529 | 0.7757 | 0.7782 | 0.7769 | 0.8075 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1