metadata
language:
- en
license: mit
base_model: microsoft/deberta-v3-large
tags:
- nycu-112-2-datamining-hw2
- generated_from_trainer
datasets:
- DandinPower/review_onlytitleandtext
metrics:
- accuracy
model-index:
- name: deberta-v3-large-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: 0.6685714285714286
deberta-v3-large-otat-recommened-hp
This model is a fine-tuned version of microsoft/deberta-v3-large on the DandinPower/review_onlytitleandtext dataset. It achieves the following results on the evaluation set:
- Loss: 0.8169
- Accuracy: 0.6686
- Macro F1: 0.6662
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: 6e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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: 50
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|---|---|---|---|---|---|
| 0.7726 | 1.14 | 500 | 0.8107 | 0.6613 | 0.6602 |
| 0.6983 | 2.29 | 1000 | 0.7739 | 0.669 | 0.6662 |
| 0.6504 | 3.43 | 1500 | 0.7891 | 0.6726 | 0.6725 |
| 0.6067 | 4.57 | 2000 | 0.8169 | 0.6686 | 0.6662 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2