metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: microsoft/deberta-v3-small
model-index:
- name: deberta-v3-small-isarcasm
results:
- task:
type: text-classification
dataset:
name: iSarcasm
type: isarcasm
split: test
metrics:
- type: f1
value: 0.44808743169398907
name: f1
- type: accuracy
value: 0.7722660653889515
name: accuracy
- type: precision
value: 0.3923444976076555
name: precision
- type: recall
value: 0.5222929936305732
name: recall
deberta-v3-small-isarcasm
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: 0.6010
- Accuracy: 0.7723
- F1: 0.4481
- Precision: 0.3923
- Recall: 0.5223
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: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 429 | 0.6567 | 0.8286 | 0.0 | 0.0 | 0.0 |
| 0.6792 | 2.0 | 858 | 0.5566 | 0.8286 | 0.625 | 0.5 | 0.8333 |
| 0.5916 | 3.0 | 1287 | 1.6155 | 0.7714 | 0.0 | 0.0 | 0.0 |
| 0.4278 | 4.0 | 1716 | 1.9964 | 0.7429 | 0.1818 | 0.2 | 0.1667 |
| 0.2417 | 5.0 | 2145 | 2.1995 | 0.7714 | 0.2 | 0.25 | 0.1667 |
Framework versions
- Transformers 4.32.0
- Pytorch 1.13.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3