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scenario-TCR_data-cl-cardiff_cl_only
haryoaw/scenario-TCR_data-cl-cardiff_cl_only
scenario-TCR_data-cl-cardiff_cl_only is a text classification model from haryoaw. 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
- Jul 27, 2024
- Updated
- Jul 27, 2024
- SHA
- 3998ff19
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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. -->
scenario-TCR_data-cl-cardiff_cl_only
This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.9878
- Accuracy: 0.5278
- F1: 0.5292
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: 66
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.09 | 250 | 1.1991 | 0.5154 | 0.5166 |
| 0.731 | 2.17 | 500 | 1.5346 | 0.5316 | 0.5279 |
| 0.731 | 3.26 | 750 | 1.6658 | 0.5255 | 0.5251 |
| 0.3491 | 4.35 | 1000 | 1.9635 | 0.5185 | 0.5189 |
| 0.3491 | 5.43 | 1250 | 2.1732 | 0.5231 | 0.5221 |
| 0.1838 | 6.52 | 1500 | 3.0035 | 0.5239 | 0.5256 |
| 0.1838 | 7.61 | 1750 | 2.9315 | 0.5239 | 0.5258 |
| 0.122 | 8.7 | 2000 | 2.8799 | 0.5039 | 0.5009 |
| 0.122 | 9.78 | 2250 | 3.0551 | 0.5023 | 0.5037 |
| 0.0746 | 10.87 | 2500 | 3.2668 | 0.5262 | 0.5279 |
| 0.0746 | 11.96 | 2750 | 3.3828 | 0.5046 | 0.5062 |
| 0.0434 | 13.04 | 3000 | 3.8937 | 0.4954 | 0.4929 |
| 0.0434 | 14.13 | 3250 | 3.7629 | 0.5224 | 0.5235 |
| 0.0369 | 15.22 | 3500 | 4.1508 | 0.4931 | 0.4880 |
| 0.0369 | 16.3 | 3750 | 4.2268 | 0.5239 | 0.5240 |
| 0.0186 | 17.39 | 4000 | 4.3692 | 0.5054 | 0.5057 |
| 0.0186 | 18.48 | 4250 | 4.3635 | 0.5108 | 0.5108 |
| 0.0156 | 19.57 | 4500 | 4.4833 | 0.5062 | 0.5039 |
| 0.0156 | 20.65 | 4750 | 4.5300 | 0.5039 | 0.5043 |
| 0.0093 | 21.74 | 5000 | 4.5612 | 0.5239 | 0.5236 |
| 0.0093 | 22.83 | 5250 | 4.7381 | 0.5208 | 0.5216 |
| 0.0088 | 23.91 | 5500 | 4.6106 | 0.5324 | 0.5334 |
| 0.0088 | 25.0 | 5750 | 4.8040 | 0.5255 | 0.5269 |
| 0.0039 | 26.09 | 6000 | 4.8616 | 0.5262 | 0.5283 |
| 0.0039 | 27.17 | 6250 | 4.9228 | 0.5231 | 0.5247 |
| 0.0052 | 28.26 | 6500 | 5.1665 | 0.5008 | 0.5012 |
| 0.0052 | 29.35 | 6750 | 4.9878 | 0.5278 | 0.5292 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Jul 27, 2024
- Updated
- Jul 27, 2024