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TTC4900Model
shivani05/TTC4900Model
TTC4900Model is a text classification model from shivani05. 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
- bert
- Access
- Public
- Created
- Nov 24, 2023
- Updated
- Nov 24, 2023
- SHA
- f4907244
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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. -->
TTC4900Model
This model is a fine-tuned version of dbmdz/bert-base-turkish-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2304
- Accuracy: 0.9341
- F1: 0.8963
- Precision: 0.9000
- Recall: 0.8989
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 2.581 | 0.88 | 50 | 2.0974 | 0.4317 | 0.2930 | 0.4400 | 0.3556 |
| 1.3915 | 1.75 | 100 | 0.6175 | 0.8590 | 0.8144 | 0.8008 | 0.8445 |
| 0.3808 | 2.63 | 150 | 0.3171 | 0.8767 | 0.8481 | 0.9359 | 0.8620 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Nov 24, 2023
- Updated
- Nov 24, 2023