---
library_name: transformers
license: mit
base_model: sercetexam9/deberta-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: deberta-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR-finetuned-augmentation-LUNAR-TAPT-macro
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# deberta-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR-finetuned-augmentation-LUNAR-TAPT-macro

This model is a fine-tuned version of [sercetexam9/deberta-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR](https://huggingface.co/sercetexam9/deberta-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1447
- F1: 0.9370
- Roc Auc: 0.9481
- Accuracy: 0.8545

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1249        | 1.0   | 421  | 0.1447          | 0.9370 | 0.9481  | 0.8545   |
| 0.1132        | 2.0   | 842  | 0.1485          | 0.9344 | 0.9512  | 0.8634   |
| 0.0924        | 3.0   | 1263 | 0.1491          | 0.9324 | 0.9528  | 0.8581   |
| 0.0679        | 4.0   | 1684 | 0.1779          | 0.9302 | 0.9433  | 0.8515   |
| 0.0844        | 5.0   | 2105 | 0.1748          | 0.9264 | 0.9429  | 0.8539   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0