metadata
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: deberta-base-finetuned-rte
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: rte
split: train
args: rte
metrics:
- name: Accuracy
type: accuracy
value: 0.6101083032490975
deberta-base-finetuned-rte
This model is a fine-tuned version of microsoft/deberta-base on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6508
- Accuracy: 0.6101
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 |
---|---|---|---|---|
No log | 1.0 | 156 | 0.7013 | 0.4982 |
No log | 2.0 | 312 | 0.6508 | 0.6101 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2