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16class_combo_2409_v5
dsmsb/16class_combo_2409_v5
16class_combo_2409_v5 is a text classification model from dsmsb. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Sep 24, 2023
- Updated
- Sep 24, 2023
- SHA
- fd5d57df
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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. -->
16class_combo_2409_v5
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1529
- Accuracy: 0.9555
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: 1e-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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 491 | 0.8079 | 0.7950 |
| 1.5652 | 2.0 | 982 | 0.5059 | 0.8689 |
| 0.7283 | 3.0 | 1473 | 0.3466 | 0.9072 |
| 0.504 | 4.0 | 1964 | 0.2646 | 0.9260 |
| 0.3862 | 5.0 | 2455 | 0.2144 | 0.9414 |
| 0.3071 | 6.0 | 2946 | 0.1885 | 0.9459 |
| 0.2554 | 7.0 | 3437 | 0.1600 | 0.9540 |
| 0.2235 | 8.0 | 3928 | 0.1529 | 0.9555 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Sep 24, 2023
- Updated
- Sep 24, 2023