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scibert-demo-10-2
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1560
- Precision: 0.3969
- Recall: 0.4380
- F1: 0.4164
- Accuracy: 0.9566
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 37 | 0.2165 | 0.4508 | 0.1585 | 0.2345 | 0.9517 |
No log | 2.0 | 74 | 0.1832 | 0.3086 | 0.3833 | 0.3419 | 0.9490 |
No log | 3.0 | 111 | 0.1580 | 0.4790 | 0.3948 | 0.4329 | 0.9596 |
No log | 4.0 | 148 | 0.1557 | 0.4141 | 0.4236 | 0.4188 | 0.9572 |
No log | 5.0 | 185 | 0.1560 | 0.3969 | 0.4380 | 0.4164 | 0.9566 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1