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---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta_rse
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_rse
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0243
- Accuracy: 0.9961
- F1: 0.9961
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8808 | 1.0 | 276 | 0.2620 | 0.9237 | 0.9242 |
| 0.3108 | 2.0 | 552 | 0.2273 | 0.9471 | 0.9470 |
| 0.2543 | 3.0 | 828 | 0.1193 | 0.9700 | 0.9700 |
| 0.1788 | 4.0 | 1104 | 0.1284 | 0.9702 | 0.9705 |
| 0.1296 | 5.0 | 1380 | 0.0549 | 0.9891 | 0.9891 |
| 0.0669 | 6.0 | 1656 | 0.0398 | 0.9927 | 0.9927 |
| 0.0658 | 7.0 | 1932 | 0.0299 | 0.9957 | 0.9957 |
| 0.0379 | 8.0 | 2208 | 0.0216 | 0.9964 | 0.9964 |
| 0.0312 | 9.0 | 2484 | 0.0243 | 0.9961 | 0.9961 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0
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