MatSciBERT-domain-classifier
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3556
- F1: 0.9027
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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
No log | 1.0 | 57 | 1.2446 | 0.8089 |
1.8516 | 2.0 | 114 | 0.6696 | 0.8354 |
1.8516 | 3.0 | 171 | 0.4096 | 0.8948 |
0.4239 | 4.0 | 228 | 0.3121 | 0.9040 |
0.4239 | 5.0 | 285 | 0.3556 | 0.9027 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.21.1
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Model tree for Navya2703/MatSciBERT-domain-classifier
Base model
allenai/scibert_scivocab_uncased