scibert-finetuned_ADEs_SonatafyAI
This model is a fine-tuned version of jsylee/scibert_scivocab_uncased-finetuned-ner on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2004
- Precision: 0.6454
- Recall: 0.6962
- F1: 0.6698
- Accuracy: 0.9095
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.2918 | 1.0 | 640 | 0.2240 | 0.6095 | 0.7148 | 0.6579 | 0.9029 |
0.2305 | 2.0 | 1280 | 0.2064 | 0.6354 | 0.6896 | 0.6614 | 0.9079 |
0.2223 | 3.0 | 1920 | 0.2031 | 0.636 | 0.6951 | 0.6642 | 0.9082 |
0.2145 | 4.0 | 2560 | 0.2010 | 0.6419 | 0.6973 | 0.6684 | 0.9089 |
0.2081 | 5.0 | 3200 | 0.2004 | 0.6454 | 0.6962 | 0.6698 | 0.9095 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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