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

# cva-quant-weighted-classifier

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: 0.1854
- Accuracy: 0.9286
- F1: 0.9231
- Precision: 0.9231
- Recall: 0.9231

## 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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6851        | 1.0   | 4    | 0.6649          | 0.7143   | 0.7333 | 0.6471    | 0.8462 |
| 0.6437        | 2.0   | 8    | 0.6270          | 0.7857   | 0.7857 | 0.7333    | 0.8462 |
| 0.6076        | 3.0   | 12   | 0.5887          | 0.8571   | 0.8462 | 0.8462    | 0.8462 |
| 0.5637        | 4.0   | 16   | 0.5442          | 0.8571   | 0.8462 | 0.8462    | 0.8462 |
| 0.5203        | 5.0   | 20   | 0.4945          | 0.8571   | 0.8462 | 0.8462    | 0.8462 |
| 0.459         | 6.0   | 24   | 0.4436          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.4076        | 7.0   | 28   | 0.3976          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.3561        | 8.0   | 32   | 0.3545          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.3095        | 9.0   | 36   | 0.3180          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.2629        | 10.0  | 40   | 0.2887          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.2282        | 11.0  | 44   | 0.2677          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.2095        | 12.0  | 48   | 0.2493          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.1808        | 13.0  | 52   | 0.2326          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.1466        | 14.0  | 56   | 0.2186          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.1408        | 15.0  | 60   | 0.2075          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.1191        | 16.0  | 64   | 0.1993          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.1185        | 17.0  | 68   | 0.1935          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.1084        | 18.0  | 72   | 0.1891          | 0.8929   | 0.8800 | 0.9167    | 0.8462 |
| 0.1119        | 19.0  | 76   | 0.1865          | 0.9286   | 0.9231 | 0.9231    | 0.9231 |
| 0.1017        | 20.0  | 80   | 0.1854          | 0.9286   | 0.9231 | 0.9231    | 0.9231 |


### Framework versions

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