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---
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
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