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scibert-lm-const-finetuned-20
This model is a fine-tuned version of allenai/scibert_scivocab_cased on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 2.0099
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.6081 | 1.0 | 118 | 2.9156 |
2.7954 | 2.0 | 236 | 2.5940 |
2.5762 | 3.0 | 354 | 2.5017 |
2.4384 | 4.0 | 472 | 2.3923 |
2.3391 | 5.0 | 590 | 2.2996 |
2.2417 | 6.0 | 708 | 2.3180 |
2.2161 | 7.0 | 826 | 2.2336 |
2.1918 | 8.0 | 944 | 2.2465 |
2.1494 | 9.0 | 1062 | 2.1871 |
2.1215 | 10.0 | 1180 | 2.1566 |
2.1015 | 11.0 | 1298 | 2.1849 |
2.05 | 12.0 | 1416 | 2.1092 |
2.0653 | 13.0 | 1534 | 2.2221 |
2.0261 | 14.0 | 1652 | 2.1572 |
2.0117 | 15.0 | 1770 | 2.1452 |
1.9845 | 16.0 | 1888 | 2.1433 |
1.9791 | 17.0 | 2006 | 2.1225 |
1.9979 | 18.0 | 2124 | 2.0777 |
1.9688 | 19.0 | 2242 | 2.1765 |
1.9873 | 20.0 | 2360 | 2.0099 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1