---
license: apache-2.0
base_model: alex-miller/ODABert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: multi-dimensional-disability
  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. -->

# multi-dimensional-disability

This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7126
- Accuracy: 0.8881
- F1: 0.8100
- Precision: 0.7556
- Recall: 0.8728

## 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-06
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.962         | 1.0   | 437  | 0.9254          | 0.8485   | 0.7272 | 0.7161    | 0.7386 |
| 0.8959        | 2.0   | 874  | 0.8276          | 0.8762   | 0.7906 | 0.7354    | 0.8546 |
| 0.8419        | 3.0   | 1311 | 0.7560          | 0.8801   | 0.7925 | 0.7517    | 0.8379 |
| 0.7452        | 4.0   | 1748 | 0.7235          | 0.8856   | 0.8048 | 0.7540    | 0.8630 |
| 0.7234        | 5.0   | 2185 | 0.7126          | 0.8881   | 0.8100 | 0.7556    | 0.8728 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2