---
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ddi_42
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ddi_42

This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2085
- Accuracy: 0.9551

## 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: 256
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 791  | 0.1986          | 0.9383   |
| 0.1723        | 2.0   | 1582 | 0.2700          | 0.9455   |
| 0.0772        | 3.0   | 2373 | 0.2085          | 0.9551   |
| 0.0516        | 4.0   | 3164 | 0.2970          | 0.9427   |
| 0.0516        | 5.0   | 3955 | 0.2620          | 0.9539   |
| 0.0341        | 6.0   | 4746 | 0.3973          | 0.9423   |
| 0.0203        | 7.0   | 5537 | 0.3637          | 0.9423   |
| 0.0146        | 8.0   | 6328 | 0.4154          | 0.9451   |
| 0.007         | 9.0   | 7119 | 0.4219          | 0.9463   |
| 0.007         | 10.0  | 7910 | 0.4098          | 0.9447   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2