File size: 2,049 Bytes
d61a2f9 |
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 |
---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_modernbert_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_model148
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_model148
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_modernbert_base](https://huggingface.co/AnonymousCS/populism_multilingual_modernbert_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5876
- Accuracy: 0.8925
- 1-f1: 0.3908
- 1-recall: 0.5484
- 1-precision: 0.3036
- Balanced Acc: 0.7320
## 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 OptimizerNames.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: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5916 | 1.0 | 31 | 0.5008 | 0.8458 | 0.3559 | 0.6774 | 0.2414 | 0.7673 |
| 0.3721 | 2.0 | 62 | 0.5412 | 0.8763 | 0.3579 | 0.5484 | 0.2656 | 0.7233 |
| 0.2282 | 3.0 | 93 | 0.5876 | 0.8925 | 0.3908 | 0.5484 | 0.3036 | 0.7320 |
### Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|