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---
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
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta_finetuned_yahoo_answers_topics
This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/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
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