File size: 2,128 Bytes
3173a5f b41fdb8 3173a5f b41fdb8 3173a5f b41fdb8 3173a5f b41fdb8 3173a5f b41fdb8 3173a5f b41fdb8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: persuasive_essays_distilbert_cased
results: []
language:
- en
---
# 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: 0.4249
- Accuracy: 0.8101
- Macro F1: 0.7662
- Claim F1: 0.665
## Intended uses & limitations
Text classification for claims on full sentences. The model perfoms better at in-domain classification. Cross-domain classification is severely limited.
## 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 dataset
- docs: 402
- tokens: 147,271
- total instances: 7,116 (65 duplicates)
- #claims: 2,108 (29.62%)
Trimmed datast used for training
- total instances: **7051** (65 duplicates removed)
- #claims: **2093** (29.68%)
- train/test split: 80/20, stratified
## 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 | 0.4369 | 0.7931 | 0.7574 | 0.6644 |
| 0.4492 | 2.0 | 706 | 0.4249 | 0.8101 | 0.7662 | 0.665 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.2 |