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---
license: mit
tags:
- generated_from_trainer
model-index:
- name: verdict-classifier
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. -->
# verdict-classifier
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1573
- F1 Macro: 0.0550
- F1 Misinformation: 0.0
- F1 Factual: 0.1650
- F1 Other: 0.0
- Prec Macro: 0.0300
- Prec Misinformation: 0.0
- Prec Factual: 0.0899
- Prec Other: 0.0
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 162525
- num_epochs: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Misinformation | F1 Factual | F1 Other | Prec Macro | Prec Misinformation | Prec Factual | Prec Other |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:----------:|:--------:|:----------:|:-------------------:|:------------:|:----------:|
| 1.2021 | 0.0 | 50 | 1.1573 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.1948 | 0.0 | 100 | 1.1569 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.1968 | 0.01 | 150 | 1.1563 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.1925 | 0.01 | 200 | 1.1554 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.2055 | 0.01 | 250 | 1.1544 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.1927 | 0.01 | 300 | 1.1531 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.1923 | 0.02 | 350 | 1.1515 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.1929 | 0.02 | 400 | 1.1496 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.1924 | 0.02 | 450 | 1.1476 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.1862 | 0.02 | 500 | 1.1454 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
| 1.1781 | 0.03 | 550 | 1.1432 | 0.0550 | 0.0 | 0.1650 | 0.0 | 0.0300 | 0.0 | 0.0899 | 0.0 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0+cu102
- Datasets 1.9.0
- Tokenizers 0.10.2
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