metadata
library_name: transformers
license: mit
base_model: m3rg-iitd/matscibert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Final_Biomaterials_ST_cems_6000
results: []
Final_Biomaterials_ST_cems_6000
This model is a fine-tuned version of m3rg-iitd/matscibert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0758
- Precision: 0.9889
- Recall: 0.9876
- F1: 0.9883
- Accuracy: 0.9887
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0304 | 1.0 | 1564 | 0.0325 | 0.9898 | 0.9862 | 0.9880 | 0.9886 |
| 0.0203 | 2.0 | 3128 | 0.0347 | 0.9894 | 0.9886 | 0.9890 | 0.9893 |
| 0.0114 | 3.0 | 4692 | 0.0397 | 0.9882 | 0.9886 | 0.9884 | 0.9888 |
| 0.0063 | 4.0 | 6256 | 0.0496 | 0.9887 | 0.9878 | 0.9883 | 0.9885 |
| 0.0048 | 5.0 | 7820 | 0.0550 | 0.9892 | 0.9876 | 0.9884 | 0.9887 |
| 0.0028 | 6.0 | 9384 | 0.0609 | 0.9886 | 0.9875 | 0.9880 | 0.9884 |
| 0.0021 | 7.0 | 10948 | 0.0658 | 0.9893 | 0.9869 | 0.9881 | 0.9886 |
| 0.0012 | 8.0 | 12512 | 0.0724 | 0.9886 | 0.9884 | 0.9885 | 0.9888 |
| 0.0012 | 9.0 | 14076 | 0.0737 | 0.9890 | 0.9878 | 0.9884 | 0.9888 |
| 0.0007 | 10.0 | 15640 | 0.0758 | 0.9889 | 0.9876 | 0.9883 | 0.9887 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0