metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: deberta-v3-small-nslp-forc-subtask1
results: []
deberta-v3-small-nslp-forc-subtask1
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2167
- Accuracy: 0.6649
- Precision: 0.6642
- Recall: 0.6649
- F1-weighted: 0.6595
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Accuracy | Precision | Recall | F1-weighted |
|---|---|---|---|---|---|---|---|
| 0.3563 | 0.77 | 2000 | 0.3333 | 0.5035 | 0.4651 | 0.5035 | 0.4562 |
| 0.2443 | 1.54 | 4000 | 0.2647 | 0.5708 | 0.5598 | 0.5708 | 0.5484 |
| 0.1736 | 2.31 | 6000 | 0.2359 | 0.6152 | 0.6105 | 0.6152 | 0.5969 |
| 0.1404 | 3.08 | 8000 | 0.2207 | 0.6424 | 0.6391 | 0.6424 | 0.6250 |
| 0.1109 | 3.85 | 10000 | 0.2181 | 0.6581 | 0.6534 | 0.6581 | 0.6490 |
| 0.0817 | 4.62 | 12000 | 0.2167 | 0.6649 | 0.6642 | 0.6649 | 0.6595 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1