metadata
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
datasets:
- yahoo_answers_topics
metrics:
- accuracy
model-index:
- name: deberta_finetuned_yahoo_answers_topics
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yahoo_answers_topics
type: yahoo_answers_topics
config: yahoo_answers_topics
split: test
args: yahoo_answers_topics
metrics:
- name: Accuracy
type: accuracy
value: 0.7073333333333334
deberta_finetuned_yahoo_answers_topics
This model is a fine-tuned version of microsoft/deberta-base on the yahoo_answers_topics dataset. It achieves the following results on the evaluation set:
- Loss: 0.9246
- Accuracy: 0.7073
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 30000
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.197 | 0.03 | 5000 | 1.1306 | 0.6511 |
1.0564 | 0.06 | 10000 | 1.0731 | 0.6690 |
0.9436 | 0.09 | 15000 | 1.0345 | 0.6864 |
1.0601 | 0.11 | 20000 | 0.9684 | 0.6925 |
0.9577 | 0.14 | 25000 | 0.9466 | 0.7015 |
0.9172 | 0.17 | 30000 | 0.9246 | 0.7073 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.14.1