metadata
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: deberta-large-finetuned-qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: qqp
split: train
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.8985901558248826
- name: F1
type: f1
value: 0.8648292232625608
deberta-large-finetuned-qqp
This model is a fine-tuned version of microsoft/deberta-large on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.2635
- Accuracy: 0.8986
- F1: 0.8648
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: 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4058 | 1.0 | 22741 | 0.3923 | 0.8496 | 0.8108 |
| 0.2347 | 2.0 | 45482 | 0.2635 | 0.8986 | 0.8648 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2