metadata
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Fine_tune_PubMedBert
results: []
Fine_tune_PubMedBert
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: 0.4669
- Precision: 0.6359
- Recall: 0.7044
- F1: 0.6684
- Accuracy: 0.8802
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: 5e-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 | 11 | 0.8690 | 0.3548 | 0.0401 | 0.0721 | 0.7691 |
| No log | 2.0 | 22 | 0.6036 | 0.6005 | 0.4635 | 0.5232 | 0.8468 |
| No log | 3.0 | 33 | 0.4788 | 0.6160 | 0.5912 | 0.6034 | 0.8678 |
| No log | 4.0 | 44 | 0.4621 | 0.5331 | 0.6898 | 0.6014 | 0.8611 |
| No log | 5.0 | 55 | 0.4319 | 0.5795 | 0.6916 | 0.6306 | 0.8681 |
| No log | 6.0 | 66 | 0.4444 | 0.5754 | 0.7099 | 0.6356 | 0.8694 |
| No log | 7.0 | 77 | 0.4472 | 0.6069 | 0.7099 | 0.6543 | 0.8756 |
| No log | 8.0 | 88 | 0.4556 | 0.6227 | 0.6898 | 0.6545 | 0.8786 |
| No log | 9.0 | 99 | 0.4613 | 0.6118 | 0.7190 | 0.6611 | 0.8767 |
| No log | 10.0 | 110 | 0.4669 | 0.6359 | 0.7044 | 0.6684 | 0.8802 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0