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scenario-TCR_data-cl-cardiff_cl_only3
haryoaw/scenario-TCR_data-cl-cardiff_cl_only3
scenario-TCR_data-cl-cardiff_cl_only3 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
- xlm-roberta
- Access
- Public
- Created
- Mar 24, 2024
- Updated
- Mar 25, 2024
- SHA
- f1e7e739
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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_only3
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.1330
- Accuracy: 0.5008
- F1: 0.5006
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: 1234
- 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 | 1.1751 | 0.4954 | 0.4934 |
| 0.8505 | 2.17 | 500 | 1.4596 | 0.5015 | 0.5021 |
| 0.8505 | 3.26 | 750 | 1.3853 | 0.5008 | 0.5006 |
| 0.4932 | 4.35 | 1000 | 1.7016 | 0.5 | 0.4986 |
| 0.4932 | 5.43 | 1250 | 1.7562 | 0.5069 | 0.5089 |
| 0.2538 | 6.52 | 1500 | 2.3494 | 0.5 | 0.4907 |
| 0.2538 | 7.61 | 1750 | 2.8723 | 0.4946 | 0.4882 |
| 0.1519 | 8.7 | 2000 | 2.3836 | 0.4838 | 0.4847 |
| 0.1519 | 9.78 | 2250 | 3.2732 | 0.5093 | 0.5101 |
| 0.1031 | 10.87 | 2500 | 3.1297 | 0.4884 | 0.4872 |
| 0.1031 | 11.96 | 2750 | 3.5334 | 0.4931 | 0.4947 |
| 0.0774 | 13.04 | 3000 | 3.6663 | 0.5108 | 0.5105 |
| 0.0774 | 14.13 | 3250 | 4.0292 | 0.4807 | 0.4811 |
| 0.0501 | 15.22 | 3500 | 4.2041 | 0.4946 | 0.4947 |
| 0.0501 | 16.3 | 3750 | 4.4274 | 0.4892 | 0.4871 |
| 0.0395 | 17.39 | 4000 | 4.1572 | 0.4961 | 0.4943 |
| 0.0395 | 18.48 | 4250 | 4.4540 | 0.5 | 0.4997 |
| 0.0279 | 19.57 | 4500 | 4.1396 | 0.5154 | 0.5166 |
| 0.0279 | 20.65 | 4750 | 4.6078 | 0.5023 | 0.5020 |
| 0.0183 | 21.74 | 5000 | 4.5365 | 0.5062 | 0.5063 |
| 0.0183 | 22.83 | 5250 | 4.8212 | 0.4915 | 0.4915 |
| 0.0133 | 23.91 | 5500 | 5.0032 | 0.4954 | 0.4952 |
| 0.0133 | 25.0 | 5750 | 4.8422 | 0.5031 | 0.5045 |
| 0.0078 | 26.09 | 6000 | 4.9698 | 0.5108 | 0.5103 |
| 0.0078 | 27.17 | 6250 | 5.1124 | 0.4985 | 0.4984 |
| 0.007 | 28.26 | 6500 | 5.1581 | 0.4900 | 0.4899 |
| 0.007 | 29.35 | 6750 | 5.1330 | 0.5008 | 0.5006 |
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
- xlm-roberta
- License
- mit
- Created
- Mar 24, 2024
- Updated
- Mar 25, 2024