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aspect_complaint_spanbert
zera09/aspect_complaint_spanbert
aspect_complaint_spanbert is a text classification model from zera09. 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
- bert
- Access
- Public
- Created
- Jun 14, 2024
- Updated
- Jun 14, 2024
- SHA
- 4d2c52d1
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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. -->
aspect_complaint_spanbert
This model is a fine-tuned version of SpanBERT/spanbert-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2032
- F1: 0.8368
- Roc Auc: 0.8935
- Accuracy: 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: 2e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 97 | 0.2810 | 0.6988 | 0.7718 | 0.0 |
| No log | 2.0 | 194 | 0.2209 | 0.7688 | 0.8260 | 0.2577 |
| No log | 3.0 | 291 | 0.2017 | 0.7958 | 0.8477 | 0.3565 |
| No log | 4.0 | 388 | 0.1882 | 0.8120 | 0.8678 | 0.4184 |
| No log | 5.0 | 485 | 0.1773 | 0.8272 | 0.8693 | 0.4416 |
| 0.2417 | 6.0 | 582 | 0.1732 | 0.8262 | 0.8792 | 0.4811 |
| 0.2417 | 7.0 | 679 | 0.1719 | 0.8331 | 0.8795 | 0.4759 |
| 0.2417 | 8.0 | 776 | 0.1722 | 0.8341 | 0.8814 | 0.5017 |
| 0.2417 | 9.0 | 873 | 0.1797 | 0.8347 | 0.8818 | 0.4923 |
| 0.2417 | 10.0 | 970 | 0.1856 | 0.8328 | 0.8859 | 0.5112 |
| 0.1287 | 11.0 | 1067 | 0.1866 | 0.8343 | 0.8868 | 0.5275 |
| 0.1287 | 12.0 | 1164 | 0.1868 | 0.8378 | 0.8898 | 0.5258 |
| 0.1287 | 13.0 | 1261 | 0.1923 | 0.8322 | 0.8864 | 0.5120 |
| 0.1287 | 14.0 | 1358 | 0.1916 | 0.8400 | 0.8929 | 0.5387 |
| 0.1287 | 15.0 | 1455 | 0.1975 | 0.8368 | 0.8919 | 0.5421 |
| 0.0781 | 16.0 | 1552 | 0.1974 | 0.8403 | 0.8951 | 0.5369 |
| 0.0781 | 17.0 | 1649 | 0.2022 | 0.8329 | 0.8911 | 0.5241 |
| 0.0781 | 18.0 | 1746 | 0.2012 | 0.8360 | 0.8921 | 0.5284 |
| 0.0781 | 19.0 | 1843 | 0.2027 | 0.8367 | 0.8936 | 0.5335 |
| 0.0781 | 20.0 | 1940 | 0.2032 | 0.8368 | 0.8935 | 0.5292 |
Framework versions
- Transformers 4.41.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Jun 14, 2024
- Updated
- Jun 14, 2024