---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: source-type-model
  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. -->

# source-type-model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6271
- F1: 0.6772

Classifies the following tags:

```
    'Cannot Determine'
    'Report/Document'
    'Named Individual'
    'Unnamed Individual'
    'Database'
    'Unnamed Group'
    'Named Group'
    'Vote/Poll'
```

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.12  | 100  | 0.7192          | 0.3792 |
| No log        | 0.25  | 200  | 0.7716          | 0.4005 |
| No log        | 0.37  | 300  | 0.7565          | 0.5297 |
| No log        | 0.49  | 400  | 0.5788          | 0.5806 |
| 0.8223        | 0.62  | 500  | 0.5402          | 0.5933 |
| 0.8223        | 0.74  | 600  | 0.5032          | 0.6666 |
| 0.8223        | 0.86  | 700  | 0.4658          | 0.6754 |
| 0.8223        | 0.99  | 800  | 0.5359          | 0.6441 |
| 0.8223        | 1.11  | 900  | 0.5295          | 0.6442 |
| 0.6009        | 1.23  | 1000 | 0.6077          | 0.6597 |
| 0.6009        | 1.35  | 1100 | 0.6169          | 0.6360 |
| 0.6009        | 1.48  | 1200 | 0.6014          | 0.6277 |
| 0.6009        | 1.6   | 1300 | 0.6382          | 0.6327 |
| 0.6009        | 1.72  | 1400 | 0.5226          | 0.6787 |
| 0.5644        | 1.85  | 1500 | 0.4922          | 0.6485 |
| 0.5644        | 1.97  | 1600 | 0.6181          | 0.6517 |
| 0.5644        | 2.09  | 1700 | 0.6106          | 0.6781 |
| 0.5644        | 2.22  | 1800 | 0.6652          | 0.6760 |
| 0.5644        | 2.34  | 1900 | 0.6252          | 0.6739 |
| 0.3299        | 2.46  | 2000 | 0.6620          | 0.6606 |
| 0.3299        | 2.59  | 2100 | 0.6317          | 0.6772 |
| 0.3299        | 2.71  | 2200 | 0.6170          | 0.6726 |
| 0.3299        | 2.83  | 2300 | 0.6400          | 0.6773 |
| 0.3299        | 2.96  | 2400 | 0.6271          | 0.6772 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3