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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: 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: 0.1539
- Accuracy: 0.9643
- F1: 0.9630
- Precision: 0.9286
- Recall: 1.0
## 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: 6e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6832 | 1.0 | 4 | 0.6577 | 0.6786 | 0.7097 | 0.6111 | 0.8462 |
| 0.6332 | 2.0 | 8 | 0.6121 | 0.8571 | 0.8462 | 0.8462 | 0.8462 |
| 0.587 | 3.0 | 12 | 0.5636 | 0.8571 | 0.8462 | 0.8462 | 0.8462 |
| 0.5308 | 4.0 | 16 | 0.5053 | 0.8571 | 0.8462 | 0.8462 | 0.8462 |
| 0.4738 | 5.0 | 20 | 0.4425 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.3972 | 6.0 | 24 | 0.3848 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.3347 | 7.0 | 28 | 0.3371 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.2769 | 8.0 | 32 | 0.2950 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.2321 | 9.0 | 36 | 0.2621 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.1847 | 10.0 | 40 | 0.2343 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.1524 | 11.0 | 44 | 0.2120 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.1374 | 12.0 | 48 | 0.1935 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.1112 | 13.0 | 52 | 0.1792 | 0.9286 | 0.9231 | 0.9231 | 0.9231 |
| 0.0881 | 14.0 | 56 | 0.1687 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0785 | 15.0 | 60 | 0.1623 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.065 | 16.0 | 64 | 0.1585 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0625 | 17.0 | 68 | 0.1570 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0566 | 18.0 | 72 | 0.1554 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0587 | 19.0 | 76 | 0.1544 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0537 | 20.0 | 80 | 0.1539 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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