---
license: apache-2.0
base_model: alex-miller/ODABert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: curated-climate-weighted
  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. -->

# curated-climate-weighted

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: 0.7523
- Accuracy: 0.7955
- F1: 0.6836
- Precision: 0.6567
- Recall: 0.7128

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7455        | 1.0   | 442  | 0.6729          | 0.7652   | 0.6691 | 0.5939    | 0.7660 |
| 0.6154        | 2.0   | 884  | 0.6549          | 0.7797   | 0.6821 | 0.6169    | 0.7627 |
| 0.5115        | 3.0   | 1326 | 0.6729          | 0.7926   | 0.6879 | 0.6445    | 0.7375 |
| 0.4169        | 4.0   | 1768 | 0.7200          | 0.7932   | 0.6835 | 0.6499    | 0.7207 |
| 0.3479        | 5.0   | 2210 | 0.7523          | 0.7955   | 0.6836 | 0.6567    | 0.7128 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1