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bert-yahoo-answers
Prezily/bert-yahoo-answers
bert-yahoo-answers is a text classification model from Prezily. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Dec 25, 2023
- Updated
- Dec 25, 2023
- SHA
- a7620f31
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
bert-yahoo-answers
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8846
- Accuracy: 0.7186
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: 60000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0979 | 0.03 | 5000 | 1.0801 | 0.6678 |
| 1.0194 | 0.06 | 10000 | 1.0599 | 0.6616 |
| 1.0349 | 0.09 | 15000 | 0.9942 | 0.6914 |
| 0.9958 | 0.11 | 20000 | 0.9737 | 0.6956 |
| 0.9643 | 0.14 | 25000 | 0.9567 | 0.7005 |
| 0.9889 | 0.17 | 30000 | 0.9357 | 0.7037 |
| 0.941 | 0.2 | 35000 | 0.9245 | 0.7072 |
| 0.9315 | 0.23 | 40000 | 0.9225 | 0.7081 |
| 0.9345 | 0.26 | 45000 | 0.9080 | 0.7136 |
| 0.9261 | 0.29 | 50000 | 0.8950 | 0.7162 |
| 0.8994 | 0.31 | 55000 | 0.8903 | 0.7189 |
| 0.8816 | 0.34 | 60000 | 0.8846 | 0.7186 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Dec 25, 2023
- Updated
- Dec 25, 2023