---
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: 0.6084
- Accuracy: 0.9116
- F1: 0.8471
- Precision: 0.8029
- Recall: 0.8966

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.9604        | 1.0   | 437  | 0.9473          | 0.8617   | 0.7483 | 0.7446    | 0.7519 |
| 0.8897        | 2.0   | 874  | 0.8169          | 0.8804   | 0.7995 | 0.7380    | 0.8721 |
| 0.8054        | 3.0   | 1311 | 0.7170          | 0.8858   | 0.8028 | 0.7601    | 0.8505 |
| 0.6757        | 4.0   | 1748 | 0.6679          | 0.8921   | 0.8164 | 0.7631    | 0.8777 |
| 0.6153        | 5.0   | 2185 | 0.6279          | 0.8992   | 0.8275 | 0.7772    | 0.8847 |
| 0.5782        | 6.0   | 2622 | 0.5773          | 0.8995   | 0.8305 | 0.7705    | 0.9008 |
| 0.5435        | 7.0   | 3059 | 0.6106          | 0.9072   | 0.8401 | 0.7937    | 0.8924 |
| 0.5333        | 8.0   | 3496 | 0.6141          | 0.9079   | 0.8435 | 0.7878    | 0.9078 |
| 0.5349        | 9.0   | 3933 | 0.6056          | 0.9097   | 0.8448 | 0.7964    | 0.8994 |
| 0.539         | 10.0  | 4370 | 0.6084          | 0.9116   | 0.8471 | 0.8029    | 0.8966 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.4.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2