metadata
library_name: transformers
license: mit
base_model: m3rg-iitd/matscibert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ST_CEMS
results: []
ST_CEMS
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: 0.0598
- Precision: 0.9368
- Recall: 0.9226
- F1: 0.9296
- Accuracy: 0.9898
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: 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 |
|---|---|---|---|---|---|---|---|
| 0.0492 | 1.0 | 569 | 0.0347 | 0.9181 | 0.9091 | 0.9136 | 0.9881 |
| 0.0177 | 2.0 | 1138 | 0.0331 | 0.9406 | 0.9177 | 0.9290 | 0.9905 |
| 0.0109 | 3.0 | 1707 | 0.0454 | 0.9116 | 0.9122 | 0.9119 | 0.9876 |
| 0.0066 | 4.0 | 2276 | 0.0454 | 0.9596 | 0.8970 | 0.9272 | 0.9896 |
| 0.0042 | 5.0 | 2845 | 0.0477 | 0.9352 | 0.9061 | 0.9204 | 0.9889 |
| 0.0027 | 6.0 | 3414 | 0.0525 | 0.9352 | 0.9146 | 0.9248 | 0.9896 |
| 0.0018 | 7.0 | 3983 | 0.0498 | 0.9405 | 0.9159 | 0.9280 | 0.9899 |
| 0.0008 | 8.0 | 4552 | 0.0555 | 0.9312 | 0.9238 | 0.9275 | 0.9896 |
| 0.0007 | 9.0 | 5121 | 0.0602 | 0.9406 | 0.9165 | 0.9284 | 0.9897 |
| 0.0006 | 10.0 | 5690 | 0.0598 | 0.9368 | 0.9226 | 0.9296 | 0.9898 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1