metadata
library_name: transformers
license: mit
base_model: m3rg-iitd/matscibert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: VF_MatSciBERT_ST_1800
results: []
VF_MatSciBERT_ST_1800
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: 0.1894
- Precision: 0.7360
- Recall: 0.7770
- F1: 0.7560
- Accuracy: 0.9556
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 30 | 0.3205 | 0.4448 | 0.2093 | 0.2847 | 0.9095 |
| No log | 2.0 | 60 | 0.2400 | 0.6346 | 0.6075 | 0.6208 | 0.9376 |
| No log | 3.0 | 90 | 0.2236 | 0.6764 | 0.7010 | 0.6885 | 0.9450 |
| No log | 4.0 | 120 | 0.1959 | 0.6664 | 0.7127 | 0.6888 | 0.9453 |
| No log | 5.0 | 150 | 0.1958 | 0.7177 | 0.7514 | 0.7342 | 0.9519 |
| No log | 6.0 | 180 | 0.1802 | 0.7180 | 0.7666 | 0.7415 | 0.9541 |
| No log | 7.0 | 210 | 0.1911 | 0.7316 | 0.7668 | 0.7488 | 0.9546 |
| No log | 8.0 | 240 | 0.1914 | 0.7384 | 0.7711 | 0.7544 | 0.9554 |
| No log | 9.0 | 270 | 0.1873 | 0.7366 | 0.7745 | 0.7551 | 0.9556 |
| No log | 10.0 | 300 | 0.1894 | 0.7360 | 0.7770 | 0.7560 | 0.9556 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1