bert-finetuned-ADEs_model_1
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: 0.1938
- Precision: 0.6759
- Recall: 0.6710
- F1: 0.6735
- Accuracy: 0.9132
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-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 |
---|---|---|---|---|---|---|---|
0.1987 | 1.0 | 640 | 0.1989 | 0.6618 | 0.6692 | 0.6655 | 0.9116 |
0.1954 | 2.0 | 1280 | 0.1953 | 0.6710 | 0.6532 | 0.6620 | 0.9132 |
0.1934 | 3.0 | 1920 | 0.1961 | 0.6586 | 0.6823 | 0.6702 | 0.9120 |
0.1879 | 4.0 | 2560 | 0.1940 | 0.6727 | 0.6718 | 0.6722 | 0.9133 |
0.1897 | 5.0 | 3200 | 0.1938 | 0.6759 | 0.6710 | 0.6735 | 0.9132 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
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