No_Prop Prop
---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-propaganda-2class
  results: []
---

# distilroberta-propaganda-2class

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the QCRI propaganda dataset. 

It achieves the following results on the evaluation set:
- Loss: 0.5087
- Acc: 0.7424

## Training and evaluation data

Training data is the 19-class QCRI propaganda data, with all propaganda classes collapsed to a single catch-all 'prop' class.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 12345
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 16
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Acc    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5737        | 1.0   | 493  | 0.5998          | 0.6515 |
| 0.4954        | 2.0   | 986  | 0.5530          | 0.7080 |
| 0.4774        | 3.0   | 1479 | 0.5331          | 0.7258 |
| 0.4846        | 4.0   | 1972 | 0.5247          | 0.7339 |
| 0.4749        | 5.0   | 2465 | 0.5392          | 0.7199 |
| 0.502         | 6.0   | 2958 | 0.5124          | 0.7466 |
| 0.457         | 7.0   | 3451 | 0.5167          | 0.7432 |
| 0.4899        | 8.0   | 3944 | 0.5160          | 0.7428 |
| 0.4833        | 9.0   | 4437 | 0.5280          | 0.7339 |
| 0.5114        | 10.0  | 4930 | 0.5112          | 0.7436 |
| 0.4419        | 11.0  | 5423 | 0.5060          | 0.7525 |
| 0.4743        | 12.0  | 5916 | 0.5031          | 0.7547 |
| 0.4597        | 13.0  | 6409 | 0.5043          | 0.7517 |
| 0.4861        | 14.0  | 6902 | 0.5055          | 0.7487 |
| 0.499         | 15.0  | 7395 | 0.5091          | 0.7419 |
| 0.501         | 16.0  | 7888 | 0.5037          | 0.7521 |
| 0.4659        | 17.0  | 8381 | 0.5087          | 0.7424 |


### Framework versions

- Transformers 4.11.2
- Pytorch 1.7.1
- Datasets 1.11.0
- Tokenizers 0.10.3
