metadata
language:
- en
license: mit
base_model: microsoft/deberta-v3-small
tags:
- nycu-112-2-datamining-hw2
- generated_from_trainer
datasets:
- DandinPower/review_onlytitleandtext
metrics:
- accuracy
model-index:
- name: deberta-v3-small-otat-recommened-hp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: DandinPower/review_onlytitleandtext
type: DandinPower/review_onlytitleandtext
metrics:
- name: Accuracy
type: accuracy
value: 0.6228571428571429
deberta-v3-small-otat-recommened-hp
This model is a fine-tuned version of microsoft/deberta-v3-small on the DandinPower/review_onlytitleandtext dataset. It achieves the following results on the evaluation set:
- Loss: 1.6500
- Accuracy: 0.6229
- Macro F1: 0.6240
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: 4.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|---|---|---|---|---|---|
| 0.8942 | 1.14 | 500 | 0.8753 | 0.6316 | 0.6330 |
| 0.7816 | 2.29 | 1000 | 0.8880 | 0.633 | 0.6216 |
| 0.7231 | 3.43 | 1500 | 0.8827 | 0.632 | 0.6322 |
| 0.6145 | 4.57 | 2000 | 0.9674 | 0.6369 | 0.6329 |
| 0.4694 | 5.71 | 2500 | 1.0903 | 0.6249 | 0.6200 |
| 0.3611 | 6.86 | 3000 | 1.2490 | 0.6216 | 0.6249 |
| 0.278 | 8.0 | 3500 | 1.4194 | 0.6201 | 0.6230 |
| 0.1689 | 9.14 | 4000 | 1.6500 | 0.6229 | 0.6240 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2