
# persuasive_essays_distilbert_cased

## Model description

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the [emnlp2017-claim-identification/persuasive_essays](https://github.com/UKPLab/emnlp2017-claim-identification) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4437
- Accuracy: 0.8044
- Macro F1: 0.7713
- Claim F1: 0.6842
 
## Intended uses & limitations

Text classification for claims on full sentences.

## Training and evaluation data

Based on [Stab and Gurevych (2017)](https://aclanthology.org/J17-3005.pdf) persuasive essays corpus, preprocessed by [Daxenberger et al. (2017)]((https://github.com/UKPLab/emnlp2017-claim-identification).

- Original docs: 402
- Original tokens: 147,271
- Original instances: 7,116 (65 duplicates)
  - Original #claims: 2,108 (29.62%)
- Used instances: 7051 (65 duplicates removed)
  - Remaining #claims: 2093 (29.68%)
- Train/Test split: 80/20


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Claim F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| No log        | 1.0   | 353  | 0.4510          | 0.8086   | 0.7795   | 0.6993   |
| 0.4526        | 2.0   | 706  | 0.4437          | 0.8044   | 0.7713   | 0.6842   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.2
{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "distilbert-base-cased", "model-index": [{"name": "persuasive_essays_distilbert_cased", "results": []}]}
transformers safetensors distilbert text-classification generated_from_trainer en base_model:distilbert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us