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scenario-TCR_data-cl-cardiff_cl_only2
haryoaw/scenario-TCR_data-cl-cardiff_cl_only2
scenario-TCR_data-cl-cardiff_cl_only2 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
- ae56f78b
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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_only2
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: 4.5723
- Accuracy: 0.5077
- F1: 0.5075
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: 1244
- 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 | 1.0569 | 0.4907 | 0.4770 |
| 0.9819 | 2.17 | 500 | 1.1934 | 0.4699 | 0.4678 |
| 0.9819 | 3.26 | 750 | 1.2411 | 0.5154 | 0.5095 |
| 0.6473 | 4.35 | 1000 | 1.5514 | 0.5069 | 0.5070 |
| 0.6473 | 5.43 | 1250 | 1.7216 | 0.5 | 0.4995 |
| 0.389 | 6.52 | 1500 | 2.1097 | 0.4807 | 0.4781 |
| 0.389 | 7.61 | 1750 | 2.1021 | 0.4769 | 0.4742 |
| 0.2296 | 8.7 | 2000 | 2.2799 | 0.4900 | 0.4912 |
| 0.2296 | 9.78 | 2250 | 2.7726 | 0.5008 | 0.5024 |
| 0.1512 | 10.87 | 2500 | 2.9023 | 0.4923 | 0.4924 |
| 0.1512 | 11.96 | 2750 | 2.9147 | 0.5062 | 0.5051 |
| 0.1123 | 13.04 | 3000 | 2.8971 | 0.5201 | 0.5203 |
| 0.1123 | 14.13 | 3250 | 3.4501 | 0.4961 | 0.4977 |
| 0.0787 | 15.22 | 3500 | 3.3121 | 0.4877 | 0.4865 |
| 0.0787 | 16.3 | 3750 | 3.2467 | 0.4961 | 0.4982 |
| 0.0574 | 17.39 | 4000 | 3.7087 | 0.4684 | 0.4655 |
| 0.0574 | 18.48 | 4250 | 3.8077 | 0.5046 | 0.5069 |
| 0.0423 | 19.57 | 4500 | 3.9974 | 0.5 | 0.5003 |
| 0.0423 | 20.65 | 4750 | 4.0173 | 0.5023 | 0.5015 |
| 0.0245 | 21.74 | 5000 | 4.0356 | 0.5 | 0.5004 |
| 0.0245 | 22.83 | 5250 | 4.2308 | 0.4992 | 0.4996 |
| 0.0177 | 23.91 | 5500 | 4.3988 | 0.4900 | 0.4885 |
| 0.0177 | 25.0 | 5750 | 4.2642 | 0.5085 | 0.5093 |
| 0.0113 | 26.09 | 6000 | 4.3893 | 0.5062 | 0.5053 |
| 0.0113 | 27.17 | 6250 | 4.5465 | 0.4977 | 0.4979 |
| 0.0076 | 28.26 | 6500 | 4.5135 | 0.5093 | 0.5098 |
| 0.0076 | 29.35 | 6750 | 4.5723 | 0.5077 | 0.5075 |
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