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all-roberta-large-v1-kitchen_and_dining-1000-16-5-oos
fathyshalab/all-roberta-large-v1-kitchen_and_dining-1000-16-5-oos
all-roberta-large-v1-kitchen_and_dining-1000-16-5-oos is a text classification model from fathyshalab. 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
- roberta
- Access
- Public
- Created
- Dec 5, 2022
- Updated
- Dec 5, 2022
- SHA
- c44ba673
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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. -->
all-roberta-large-v1-kitchen_and_dining-1000-16-5-oos
This model is a fine-tuned version of sentence-transformers/all-roberta-large-v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.4398
- Accuracy: 0.2308
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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.0631 | 1.0 | 1 | 4.8365 | 0.1509 |
| 4.2899 | 2.0 | 2 | 4.6738 | 0.2041 |
| 3.7697 | 3.0 | 3 | 4.5378 | 0.2189 |
| 3.1321 | 4.0 | 4 | 4.4398 | 0.2308 |
| 2.7818 | 5.0 | 5 | 4.3885 | 0.2308 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Dec 5, 2022
- Updated
- Dec 5, 2022