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distilbert-base-uncased-xsum-factuality
ernlavr/distilbert-base-uncased-xsum-factuality
distilbert-base-uncased-xsum-factuality is a text classification model from ernlavr. 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 18, 2023
- Updated
- Jan 4, 2024
- SHA
- 416c13bd
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Base models
Datasets
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. -->
Distilbert-base-uncased-xsum-factuality
This model is a fine-tuned version of distilbert-base-uncased on the XSum-Factuality dataset. You can view more implementation details as part of this GitHub repository. It achieves the following results on the evaluation set:
- Loss: 0.6850
- Accuracy: 0.6332
- F1: 0.6212
- Precision: 0.6526
- Recall: 0.6332
Weights and Biases Documentation
View the full run on Weights & Biases
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: 1e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6904 | 6.93 | 1040 | 0.6850 | 0.6332 | 0.6212 | 0.6526 | 0.6332 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Languages
- en
- Created
- Dec 18, 2023
- Updated
- Jan 4, 2024