File size: 2,654 Bytes
bbb88fa | 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 74 75 | ---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_111
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_111
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3306
- Accuracy: 0.8813
- 1-f1: 0.3077
- 1-recall: 0.9091
- 1-precision: 0.1852
- Balanced Acc: 0.8948
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.7516 | 1.0 | 10 | 0.6561 | 0.9631 | 0.0 | 0.0 | 0.0 | 0.4959 |
| 0.6877 | 2.0 | 20 | 0.5274 | 0.9710 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6049 | 3.0 | 30 | 0.5956 | 0.8707 | 0.1967 | 0.5455 | 0.12 | 0.7129 |
| 0.5518 | 4.0 | 40 | 0.4287 | 0.8206 | 0.2093 | 0.8182 | 0.12 | 0.8194 |
| 0.4657 | 5.0 | 50 | 0.5567 | 0.7018 | 0.1630 | 1.0 | 0.0887 | 0.8465 |
| 0.5129 | 6.0 | 60 | 0.2019 | 0.9261 | 0.3636 | 0.7273 | 0.2424 | 0.8297 |
| 0.4573 | 7.0 | 70 | 0.1564 | 0.8997 | 0.3214 | 0.8182 | 0.2 | 0.8602 |
| 0.2978 | 8.0 | 80 | 0.3465 | 0.8971 | 0.3158 | 0.8182 | 0.1957 | 0.8588 |
| 0.1075 | 9.0 | 90 | 0.3306 | 0.8813 | 0.3077 | 0.9091 | 0.1852 | 0.8948 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|