---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
pipeline_tag: text-classification
model-index:
- name: fator-argument-quality
  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. -->

# fator-argument-quality

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5797
- Accuracy: 0.8014
- F1 Macro: 0.5806
- F1 Weighted: 0.7459

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 0.5548        | 1.0   | 558  | 0.5412          | 0.7741   | 0.3669   | 0.7188      |
| 0.4892        | 2.0   | 1116 | 0.5830          | 0.7866   | 0.3644   | 0.7055      |
| 0.4455        | 3.0   | 1674 | 0.5797          | 0.7814   | 0.4606   | 0.7449      |
| 0.3561        | 4.0   | 2232 | 0.6330          | 0.7902   | 0.4996    | 0.7457      |
| 0.3084        | 5.0   | 2790 | 0.6744          | 0.8057   | 0.5806   | 0.7459       |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2