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deberta-v3-base-amazon-reviews-multi-fp16
thainq107/deberta-v3-base-amazon-reviews-multi-fp16
deberta-v3-base-amazon-reviews-multi-fp16 is a text classification model from thainq107. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Sep 8, 2023
- Updated
- Sep 8, 2023
- SHA
- 431da019
Try a prompt
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. -->
deberta-v3-base-amazon-reviews-multi-fp16
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9190
- Accuracy: 0.5976
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9134 | 1.0 | 6250 | 0.9276 | 0.6 |
| 0.8412 | 2.0 | 12500 | 0.9287 | 0.6082 |
| 0.7523 | 3.0 | 18750 | 0.9500 | 0.6078 |
| 0.6247 | 4.0 | 25000 | 1.0481 | 0.5984 |
| 0.51 | 5.0 | 31250 | 1.1977 | 0.6016 |
Framework versions
- Transformers 4.27.1
- Pytorch 2.0.1
- Datasets 2.9.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Sep 8, 2023
- Updated
- Sep 8, 2023