ChatGPT_Project
This model is a fine-tuned version of bert-base-cased on the wnut_17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3070
- Precision: 0.3690
- Recall: 0.1149
- F1: 0.1753
- Accuracy: 0.9320
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: 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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 213 | 0.4153 | 0.0 | 0.0 | 0.0 | 0.9256 |
No log | 2.0 | 426 | 0.3484 | 0.0 | 0.0 | 0.0 | 0.9256 |
0.6399 | 3.0 | 639 | 0.3303 | 0.2222 | 0.0037 | 0.0073 | 0.9256 |
0.6399 | 4.0 | 852 | 0.3233 | 0.2179 | 0.0158 | 0.0294 | 0.9269 |
0.2004 | 5.0 | 1065 | 0.3164 | 0.3152 | 0.0482 | 0.0836 | 0.9286 |
0.2004 | 6.0 | 1278 | 0.3148 | 0.3421 | 0.0723 | 0.1194 | 0.9299 |
0.2004 | 7.0 | 1491 | 0.3100 | 0.3653 | 0.0918 | 0.1467 | 0.9309 |
0.1861 | 8.0 | 1704 | 0.3083 | 0.3522 | 0.0982 | 0.1536 | 0.9312 |
0.1861 | 9.0 | 1917 | 0.3057 | 0.3663 | 0.1168 | 0.1771 | 0.9320 |
0.1782 | 10.0 | 2130 | 0.3070 | 0.3690 | 0.1149 | 0.1753 | 0.9320 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
google-bert/bert-base-cased
Finetuned
this model
Dataset used to train galaxy78/ChatGPT_Project
Evaluation results
- Precision on wnut_17test set self-reported0.369
- Recall on wnut_17test set self-reported0.115
- F1 on wnut_17test set self-reported0.175
- Accuracy on wnut_17test set self-reported0.932