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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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