File size: 2,151 Bytes
e64beca |
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_base_cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_309
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_bsample_309
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_cased](https://huggingface.co/AnonymousCS/populism_english_bert_base_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9426
- Accuracy: 0.6636
- 1-f1: 0.3125
- 1-recall: 1.0
- 1-precision: 0.1852
- Balanced Acc: 0.8179
## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1146 | 1.0 | 6 | 0.8631 | 0.6208 | 0.2874 | 1.0 | 0.1678 | 0.7947 |
| 0.0541 | 2.0 | 12 | 0.6813 | 0.7095 | 0.3448 | 1.0 | 0.2083 | 0.8427 |
| 0.0249 | 3.0 | 18 | 1.0492 | 0.5994 | 0.2762 | 1.0 | 0.1603 | 0.7831 |
| 0.0308 | 4.0 | 24 | 0.9426 | 0.6636 | 0.3125 | 1.0 | 0.1852 | 0.8179 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|