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---
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
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