---
license: apache-2.0
base_model: alex-miller/ODABert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: iati-gender-multi-classifier-weighted-minitest
  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. -->

# iati-gender-multi-classifier-weighted-minitest

This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6625
- Accuracy: 0.8256
- F1: 0.6997
- Precision: 0.6138
- Recall: 0.8135

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.9142        | 1.0   | 616  | 0.7573          | 0.7352   | 0.5803 | 0.4802    | 0.7331 |
| 0.7431        | 2.0   | 1232 | 0.6871          | 0.7973   | 0.6652 | 0.5661    | 0.8062 |
| 0.6934        | 3.0   | 1848 | 0.6713          | 0.8160   | 0.6902 | 0.5955    | 0.8208 |
| 0.6631        | 4.0   | 2464 | 0.6609          | 0.8187   | 0.6944 | 0.5997    | 0.8245 |
| 0.6341        | 5.0   | 3080 | 0.6589          | 0.8237   | 0.6956 | 0.6117    | 0.8062 |
| 0.6143        | 6.0   | 3696 | 0.6551          | 0.8205   | 0.6970 | 0.6027    | 0.8263 |
| 0.5931        | 7.0   | 4312 | 0.6597          | 0.8201   | 0.6893 | 0.6061    | 0.7989 |
| 0.5773        | 8.0   | 4928 | 0.6579          | 0.8224   | 0.6963 | 0.6076    | 0.8154 |
| 0.5652        | 9.0   | 5544 | 0.6613          | 0.8233   | 0.6984 | 0.6087    | 0.8190 |
| 0.5597        | 10.0  | 6160 | 0.6625          | 0.8256   | 0.6997 | 0.6138    | 0.8135 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1