metadata
license: mit
base_model: m3rg-iitd/matscibert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: MatSciBERT_BIOMAT_NER1800
results: []
MatSciBERT_BIOMAT_NER1800
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: 0.1788
- Precision: 0.9841
- Recall: 0.9758
- F1: 0.9799
- Accuracy: 0.9728
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.186 | 1.0 | 869 | 0.0890 | 0.9831 | 0.9762 | 0.9796 | 0.9730 |
| 0.0519 | 2.0 | 1738 | 0.0944 | 0.9834 | 0.9773 | 0.9803 | 0.9744 |
| 0.0293 | 3.0 | 2607 | 0.1101 | 0.9832 | 0.9748 | 0.9790 | 0.9721 |
| 0.0185 | 4.0 | 3476 | 0.1348 | 0.9823 | 0.9752 | 0.9788 | 0.9721 |
| 0.0086 | 5.0 | 4345 | 0.1421 | 0.9823 | 0.9746 | 0.9785 | 0.9715 |
| 0.0054 | 6.0 | 5214 | 0.1755 | 0.9835 | 0.9719 | 0.9777 | 0.9693 |
| 0.0032 | 7.0 | 6083 | 0.1706 | 0.9831 | 0.9735 | 0.9783 | 0.9709 |
| 0.0027 | 8.0 | 6952 | 0.1774 | 0.9840 | 0.9756 | 0.9798 | 0.9729 |
| 0.0017 | 9.0 | 7821 | 0.1825 | 0.9841 | 0.9749 | 0.9795 | 0.9717 |
| 0.001 | 10.0 | 8690 | 0.1788 | 0.9841 | 0.9758 | 0.9799 | 0.9728 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1