---
license: apache-2.0
base_model: alex-miller/ODABert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: cdp-multi-classifier-sub-classes-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. -->

# cdp-multi-classifier-sub-classes-weighted

This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert).
It achieves the following results on the evaluation set:
- Loss: 0.6494
- Accuracy: 0.8423
- F1: 0.7847
- Precision: 0.7488
- Recall: 0.8243

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8824        | 1.0   | 206  | 0.9109          | 0.6793   | 0.5494 | 0.5385    | 0.5607 |
| 0.816         | 2.0   | 412  | 0.8348          | 0.7865   | 0.7127 | 0.6712    | 0.7597 |
| 0.7455        | 3.0   | 618  | 0.7694          | 0.7712   | 0.7053 | 0.64      | 0.7855 |
| 0.6808        | 4.0   | 824  | 0.7323          | 0.7874   | 0.7217 | 0.6638    | 0.7907 |
| 0.6246        | 5.0   | 1030 | 0.6920          | 0.7829   | 0.7175 | 0.6567    | 0.7907 |
| 0.5689        | 6.0   | 1236 | 0.6926          | 0.7874   | 0.7230 | 0.6624    | 0.7959 |
| 0.5237        | 7.0   | 1442 | 0.6642          | 0.8072   | 0.7476 | 0.6876    | 0.8191 |
| 0.4842        | 8.0   | 1648 | 0.6419          | 0.8081   | 0.7461 | 0.6925    | 0.8088 |
| 0.4519        | 9.0   | 1854 | 0.6498          | 0.8225   | 0.7612 | 0.7169    | 0.8114 |
| 0.4264        | 10.0  | 2060 | 0.6496          | 0.8315   | 0.7728 | 0.7294    | 0.8217 |
| 0.4078        | 11.0  | 2266 | 0.6669          | 0.8378   | 0.7800 | 0.7401    | 0.8243 |
| 0.398         | 12.0  | 2472 | 0.6508          | 0.8405   | 0.7828 | 0.7453    | 0.8243 |
| 0.3808        | 13.0  | 2678 | 0.6539          | 0.8387   | 0.7809 | 0.7419    | 0.8243 |
| 0.3757        | 14.0  | 2884 | 0.6497          | 0.8423   | 0.7847 | 0.7488    | 0.8243 |
| 0.3691        | 15.0  | 3090 | 0.6494          | 0.8423   | 0.7847 | 0.7488    | 0.8243 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1