File size: 2,252 Bytes
1949b7a | 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 | ---
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_333
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_333
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: 1.7774
- Accuracy: 0.9201
- 1-f1: 0.2564
- 1-recall: 0.1562
- 1-precision: 0.7143
- Balanced Acc: 0.5751
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5971 | 1.0 | 23 | 0.3359 | 0.8402 | 0.4821 | 0.8438 | 0.3375 | 0.8418 |
| 0.2685 | 2.0 | 46 | 0.3264 | 0.8320 | 0.5041 | 0.9688 | 0.3407 | 0.8937 |
| 0.13 | 3.0 | 69 | 0.4028 | 0.8843 | 0.5000 | 0.6562 | 0.4038 | 0.7813 |
| 0.1104 | 4.0 | 92 | 0.4979 | 0.8733 | 0.5208 | 0.7812 | 0.3906 | 0.8317 |
| 0.4235 | 5.0 | 115 | 1.7774 | 0.9201 | 0.2564 | 0.1562 | 0.7143 | 0.5751 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|