metadata
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-large-ReqORNot
results: []
deberta-large-ReqORNot
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5297
- Accuracy: 0.9135
- Weighted precision: 0.9135
- Weighted recall: 0.9135
- Weighted f1: 0.9134
- Macro precision: 0.9135
- Macro recall: 0.9128
- Macro f1: 0.9131
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: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted precision | Weighted recall | Weighted f1 | Macro precision | Macro recall | Macro f1 |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.4826 | 1.0 | 1896 | 0.4286 | 0.9020 | 0.9020 | 0.9020 | 0.9019 | 0.9018 | 0.9014 | 0.9016 |
| 0.3429 | 2.0 | 3792 | 0.4274 | 0.9077 | 0.9091 | 0.9077 | 0.9078 | 0.9076 | 0.9089 | 0.9076 |
| 0.1299 | 3.0 | 5688 | 0.5297 | 0.9135 | 0.9135 | 0.9135 | 0.9134 | 0.9135 | 0.9128 | 0.9131 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2