---
base_model: allenai/biomed_roberta_base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biomed_roberta_all_deep
  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. -->

# biomed_roberta_all_deep

This model is a fine-tuned version of [allenai/biomed_roberta_base](https://huggingface.co/allenai/biomed_roberta_base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7519
- Precision: 0.6732
- Recall: 0.7142
- F1: 0.6931
- Accuracy: 0.8255

## 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: 2e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 363  | 0.5600          | 0.6059    | 0.6773 | 0.6396 | 0.8131   |
| 0.7102        | 2.0   | 726  | 0.5290          | 0.6310    | 0.7172 | 0.6713 | 0.8248   |
| 0.4147        | 3.0   | 1089 | 0.5253          | 0.6620    | 0.7075 | 0.6840 | 0.8289   |
| 0.4147        | 4.0   | 1452 | 0.5572          | 0.6664    | 0.7062 | 0.6857 | 0.8263   |
| 0.3081        | 5.0   | 1815 | 0.5942          | 0.6615    | 0.7127 | 0.6862 | 0.8244   |
| 0.231         | 6.0   | 2178 | 0.6393          | 0.6745    | 0.7064 | 0.6901 | 0.8268   |
| 0.1864        | 7.0   | 2541 | 0.6771          | 0.6769    | 0.7050 | 0.6907 | 0.8250   |
| 0.1864        | 8.0   | 2904 | 0.7091          | 0.6708    | 0.7120 | 0.6908 | 0.8263   |
| 0.1523        | 9.0   | 3267 | 0.7463          | 0.6702    | 0.7159 | 0.6923 | 0.8255   |
| 0.1336        | 10.0  | 3630 | 0.7519          | 0.6732    | 0.7142 | 0.6931 | 0.8255   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1