metadata
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: pretoxtm-sentence-classifier
results: []
pretoxtm-sentence-classifier
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0802
- Precision: 0.9778
- Recall: 0.9801
- Accuracy: 0.9795
- F1: 0.9789
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: 7.755382954990098e-06
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 257 | 0.1410 | 0.9593 | 0.9684 | 0.9636 | 0.9628 |
| 0.1997 | 2.0 | 514 | 0.0802 | 0.9778 | 0.9801 | 0.9795 | 0.9789 |
| 0.1997 | 3.0 | 771 | 0.1103 | 0.9824 | 0.9848 | 0.9841 | 0.9836 |
| 0.0514 | 4.0 | 1028 | 0.1139 | 0.9798 | 0.9829 | 0.9818 | 0.9813 |
| 0.0514 | 5.0 | 1285 | 0.1208 | 0.9804 | 0.9821 | 0.9818 | 0.9812 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2