---
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
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-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3300
- Accuracy: 0.9547

## 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  | 0.1947          | 0.9471   |
| 0.1709        | 2.0   | 1582 | 0.2474          | 0.9527   |
| 0.0734        | 3.0   | 2373 | 0.2485          | 0.9475   |
| 0.0475        | 4.0   | 3164 | 0.2686          | 0.9499   |
| 0.0475        | 5.0   | 3955 | 0.3196          | 0.9475   |
| 0.0284        | 6.0   | 4746 | 0.3014          | 0.9527   |
| 0.0194        | 7.0   | 5537 | 0.3125          | 0.9523   |
| 0.0133        | 8.0   | 6328 | 0.3641          | 0.9491   |
| 0.0065        | 9.0   | 7119 | 0.3300          | 0.9547   |
| 0.0065        | 10.0  | 7910 | 0.3502          | 0.9543   |


### Framework versions

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