metadata
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-v3-large-271-ver1
results: []
deberta-v3-large-271-ver1
This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1014
- Precision: 0.9702
- Recall: 0.9702
- F1: 0.9702
- Accuracy: 0.9702
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: 12
- eval_batch_size: 12
- 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 |
|---|---|---|---|---|---|---|---|
| 0.2626 | 1.0 | 896 | 0.1186 | 0.9561 | 0.9561 | 0.9561 | 0.9561 |
| 0.0699 | 2.0 | 1792 | 0.1014 | 0.9702 | 0.9702 | 0.9702 | 0.9702 |
| 0.0352 | 3.0 | 2688 | 0.1217 | 0.9680 | 0.9680 | 0.9680 | 0.9680 |
| 0.0115 | 4.0 | 3584 | 0.1857 | 0.9672 | 0.9672 | 0.9672 | 0.9672 |
| 0.0083 | 5.0 | 4480 | 0.2098 | 0.9680 | 0.9680 | 0.9680 | 0.9680 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1