metadata
library_name: transformers
license: mit
base_model: m3rg-iitd/matscibert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: MatSciBERT_ST_DA_100
results: []
MatSciBERT_ST_DA_100
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: 0.2043
- Precision: 0.9627
- Recall: 0.9693
- F1: 0.9660
- Accuracy: 0.9561
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 59 | 0.2685 | 0.9263 | 0.9420 | 0.9341 | 0.9213 |
| No log | 2.0 | 118 | 0.1935 | 0.9477 | 0.9573 | 0.9524 | 0.9429 |
| No log | 3.0 | 177 | 0.2043 | 0.9558 | 0.9669 | 0.9613 | 0.9506 |
| No log | 4.0 | 236 | 0.1769 | 0.9596 | 0.9701 | 0.9648 | 0.9554 |
| No log | 5.0 | 295 | 0.1789 | 0.9619 | 0.9686 | 0.9652 | 0.9561 |
| No log | 6.0 | 354 | 0.1916 | 0.9620 | 0.9683 | 0.9651 | 0.9557 |
| No log | 7.0 | 413 | 0.1955 | 0.9623 | 0.9685 | 0.9654 | 0.9559 |
| No log | 8.0 | 472 | 0.2002 | 0.9627 | 0.9713 | 0.9670 | 0.9575 |
| 0.1044 | 9.0 | 531 | 0.2033 | 0.9632 | 0.9698 | 0.9665 | 0.9566 |
| 0.1044 | 10.0 | 590 | 0.2043 | 0.9627 | 0.9693 | 0.9660 | 0.9561 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1