---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: deberta-v3-base_smcalflow-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. -->

# deberta-v3-base_smcalflow-classifier

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: 0.0679
- F1 Micro: 0.7989
- F1 Macro: 0.1141
- Exact Match: 0.0625

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Exact Match |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 0.0820        | 1.0   | 656  | 0.1066          | 0.5700   | 0.0268   | 0.0         |
| 0.0632        | 2.0   | 1312 | 0.0815          | 0.7238   | 0.0548   | 0.0         |
| 0.0491        | 3.0   | 1968 | 0.0724          | 0.7640   | 0.0881   | 0.0111      |
| 0.0417        | 4.0   | 2624 | 0.0686          | 0.7921   | 0.1111   | 0.0486      |
| 0.0387        | 5.0   | 3280 | 0.0679          | 0.7989   | 0.1141   | 0.0625      |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2