metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_2e-05_ES2
results: []
tmvar_2e-05_ES2
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0184
- Precision: 0.8368
- Recall: 0.8595
- F1: 0.848
- Accuracy: 0.9962
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
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.5018 | 1.47 | 25 | 0.1002 | 0.0 | 0.0 | 0.0 | 0.9843 |
| 0.0852 | 2.94 | 50 | 0.0509 | 0.9286 | 0.0703 | 0.1307 | 0.9852 |
| 0.0373 | 4.41 | 75 | 0.0283 | 0.5485 | 0.6108 | 0.5780 | 0.9918 |
| 0.0256 | 5.88 | 100 | 0.0204 | 0.6429 | 0.7297 | 0.6835 | 0.9938 |
| 0.0123 | 7.35 | 125 | 0.0188 | 0.8063 | 0.8324 | 0.8191 | 0.9956 |
| 0.008 | 8.82 | 150 | 0.0171 | 0.7979 | 0.8324 | 0.8148 | 0.9958 |
| 0.0047 | 10.29 | 175 | 0.0158 | 0.8010 | 0.8919 | 0.8440 | 0.9962 |
| 0.0037 | 11.76 | 200 | 0.0171 | 0.8511 | 0.8649 | 0.8579 | 0.9964 |
| 0.0025 | 13.24 | 225 | 0.0184 | 0.8368 | 0.8595 | 0.848 | 0.9962 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2