metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: output
results: []
output
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0022
- Name Student Precision: 0.9737
- Name Student Recall: 1.0
- Name Student F1: 0.9867
- Name Student Number: 37
- Overall Precision: 0.9737
- Overall Recall: 1.0
- Overall F1: 0.9867
- Overall Accuracy: 0.9975
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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Name Student Precision | Name Student Recall | Name Student F1 | Name Student Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0002 | 1.0 | 400 | 0.0061 | 0.9737 | 1.0 | 0.9867 | 37 | 0.9737 | 1.0 | 0.9867 | 0.9975 |
| 0.0001 | 2.0 | 800 | 0.0022 | 0.9737 | 1.0 | 0.9867 | 37 | 0.9737 | 1.0 | 0.9867 | 0.9975 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2