metadata
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: rubert-tiny2-ner-drugname
results: []
rubert-tiny2-ner-drugname
This model is a fine-tuned version of cointegrated/rubert-tiny2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0549
- Precision: 0.7232
- Recall: 0.7690
- F1: 0.7454
- Accuracy: 0.9883
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: 0.0002
- train_batch_size: 64
- eval_batch_size: 64
- 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 | 61 | 0.0493 | 0.6413 | 0.7468 | 0.6901 | 0.9833 |
| No log | 2.0 | 122 | 0.0417 | 0.6406 | 0.8291 | 0.7228 | 0.9855 |
| No log | 3.0 | 183 | 0.0387 | 0.7588 | 0.7468 | 0.7528 | 0.9879 |
| No log | 4.0 | 244 | 0.0396 | 0.7385 | 0.7595 | 0.7488 | 0.9883 |
| No log | 5.0 | 305 | 0.0425 | 0.6897 | 0.7595 | 0.7229 | 0.9874 |
| No log | 6.0 | 366 | 0.0465 | 0.6991 | 0.7722 | 0.7338 | 0.9876 |
| No log | 7.0 | 427 | 0.0487 | 0.7062 | 0.7911 | 0.7463 | 0.9877 |
| No log | 8.0 | 488 | 0.0521 | 0.7076 | 0.7658 | 0.7356 | 0.9882 |
| 0.0306 | 9.0 | 549 | 0.0540 | 0.7262 | 0.7722 | 0.7485 | 0.9883 |
| 0.0306 | 10.0 | 610 | 0.0549 | 0.7232 | 0.7690 | 0.7454 | 0.9883 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1