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: 0.2750
- Accuracy: 0.9261
- F1: 0.9259
- Precision: 0.9311
- Recall: 0.9207
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 |
---|---|---|---|---|---|---|---|
0.2484 | 1.0 | 30000 | 0.2765 | 0.9192 | 0.9209 | 0.9039 | 0.9386 |
0.2141 | 2.0 | 60000 | 0.2750 | 0.9261 | 0.9259 | 0.9311 | 0.9207 |
0.1991 | 3.0 | 90000 | 0.2952 | 0.9271 | 0.9275 | 0.9248 | 0.9303 |
0.1661 | 4.0 | 120000 | 0.3409 | 0.9274 | 0.9275 | 0.9284 | 0.9266 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3