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my_RD_model
TValentine/my_RD_model
my_RD_model is a text classification model from TValentine. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Jul 20, 2023
- Updated
- Sep 15, 2023
- SHA
- 88622c9b
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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. -->
my_RD_model
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6033
- Accuracy: 0.8822
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.2765 | 1.0 | 1109 | 0.2861 | 0.8926 |
| 0.2254 | 2.0 | 2218 | 0.3469 | 0.8820 |
| 0.1552 | 3.0 | 3327 | 0.4630 | 0.8721 |
| 0.108 | 4.0 | 4436 | 0.5382 | 0.8845 |
| 0.0853 | 5.0 | 5545 | 0.6033 | 0.8822 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Created
- Jul 20, 2023
- Updated
- Sep 15, 2023