---
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: 0.7162
- F1: 0.4315

## 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  | 1.3490          | 0.0956 |
| No log        | 0.25  | 200  | 1.4751          | 0.0956 |
| No log        | 0.37  | 300  | 0.9687          | 0.2427 |
| No log        | 0.49  | 400  | 1.0625          | 0.1891 |
| 1.2336        | 0.62  | 500  | 1.0954          | 0.1949 |
| 1.2336        | 0.74  | 600  | 0.9969          | 0.3080 |
| 1.2336        | 0.86  | 700  | 0.9171          | 0.3175 |
| 1.2336        | 0.99  | 800  | 0.9600          | 0.3136 |
| 1.2336        | 1.11  | 900  | 0.9637          | 0.3161 |
| 1.0269        | 1.23  | 1000 | 0.9592          | 0.3257 |
| 1.0269        | 1.35  | 1100 | 0.9117          | 0.3342 |
| 1.0269        | 1.48  | 1200 | 0.8891          | 0.3205 |
| 1.0269        | 1.6   | 1300 | 0.8136          | 0.3375 |
| 1.0269        | 1.72  | 1400 | 0.9676          | 0.3300 |
| 0.8592        | 1.85  | 1500 | 0.8778          | 0.3316 |
| 0.8592        | 1.97  | 1600 | 0.8407          | 0.3379 |
| 0.8592        | 2.09  | 1700 | 0.8409          | 0.3369 |
| 0.8592        | 2.22  | 1800 | 0.8818          | 0.3343 |
| 0.8592        | 2.34  | 1900 | 0.9259          | 0.3386 |
| 0.7521        | 2.46  | 2000 | 0.9419          | 0.3380 |
| 0.7521        | 2.59  | 2100 | 0.8050          | 0.3474 |
| 0.7521        | 2.71  | 2200 | 0.7773          | 0.4053 |
| 0.7521        | 2.83  | 2300 | 0.7114          | 0.4337 |
| 0.7521        | 2.96  | 2400 | 0.7162          | 0.4315 |


### Framework versions

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