File size: 2,141 Bytes
b610940 8e8630a b610940 8e8630a b610940 8e8630a b610940 | 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 | ---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_large_cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_317
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. -->
# populism_classifier_317
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_cased](https://huggingface.co/AnonymousCS/populism_english_bert_large_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6002
- Accuracy: 0.9557
- 1-f1: 0.5778
- 1-recall: 0.5417
- 1-precision: 0.6190
- Balanced Acc: 0.7610
## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1895 | 1.0 | 27 | 0.2592 | 0.9487 | 0.6333 | 0.7917 | 0.5278 | 0.8748 |
| 0.189 | 2.0 | 54 | 0.2613 | 0.9347 | 0.6 | 0.875 | 0.4565 | 0.9066 |
| 0.0758 | 3.0 | 81 | 0.3632 | 0.9464 | 0.5490 | 0.5833 | 0.5185 | 0.7756 |
| 0.4068 | 4.0 | 108 | 0.6002 | 0.9557 | 0.5778 | 0.5417 | 0.6190 | 0.7610 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|