metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: im-bin-tf-abstr
results: []
im-bin-tf-abstr
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2870
- Accuracy: 0.893
- F1: 0.8996
- Precision: 0.8822
- Recall: 0.9177
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: 1e-05
- 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: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.3099 | 1.0 | 1000 | 0.2870 | 0.893 | 0.8996 | 0.8822 | 0.9177 |
0.2679 | 2.0 | 2000 | 0.3312 | 0.9005 | 0.9032 | 0.9188 | 0.8880 |
0.2308 | 3.0 | 3000 | 0.4214 | 0.899 | 0.9048 | 0.8914 | 0.9187 |
0.1504 | 4.0 | 4000 | 0.4381 | 0.9015 | 0.9051 | 0.9117 | 0.8986 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3