metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: irony_fr_Canada
results: []
irony_fr_Canada
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0034
- Accuracy: 0.6647
- Precision: 0.4748
- Recall: 0.6111
- F1: 0.5344
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: 5e-06
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0044 | 1.0 | 65 | 0.0043 | 0.6764 | 0.4 | 0.0556 | 0.0976 |
| 0.0042 | 2.0 | 130 | 0.0042 | 0.5773 | 0.4 | 0.6852 | 0.5051 |
| 0.0039 | 3.0 | 195 | 0.0040 | 0.6618 | 0.4574 | 0.3981 | 0.4257 |
| 0.0037 | 4.0 | 260 | 0.0036 | 0.6356 | 0.4422 | 0.6019 | 0.5098 |
| 0.003 | 5.0 | 325 | 0.0033 | 0.5889 | 0.4108 | 0.7037 | 0.5188 |
| 0.0026 | 6.0 | 390 | 0.0033 | 0.6647 | 0.4706 | 0.5185 | 0.4934 |
| 0.0022 | 7.0 | 455 | 0.0034 | 0.6647 | 0.4748 | 0.6111 | 0.5344 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1