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README.md
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---
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license: mit
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base_model: microsoft/deberta-base
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tags:
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- generated_from_trainer
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datasets:
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- yahoo_answers_topics
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metrics:
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- accuracy
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model-index:
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- name: deberta_finetuned_yahoo_answers_topics
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: yahoo_answers_topics
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type: yahoo_answers_topics
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config: yahoo_answers_topics
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split: test
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args: yahoo_answers_topics
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7073333333333334
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# deberta_finetuned_yahoo_answers_topics
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This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the yahoo_answers_topics dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9246
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- Accuracy: 0.7073
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- training_steps: 30000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 1.197 | 0.03 | 5000 | 1.1306 | 0.6511 |
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| 1.0564 | 0.06 | 10000 | 1.0731 | 0.6690 |
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| 0.9436 | 0.09 | 15000 | 1.0345 | 0.6864 |
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| 1.0601 | 0.11 | 20000 | 0.9684 | 0.6925 |
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| 0.9577 | 0.14 | 25000 | 0.9466 | 0.7015 |
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| 0.9172 | 0.17 | 30000 | 0.9246 | 0.7073 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.0.0
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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