metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: xlm-roberta-base
model-index:
- name: xlm-roberta-base_single_finetuned_on_cedr_augmented
results: []
xlm-roberta-base_single_finetuned_on_cedr_augmented
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4650
- Accuracy: 0.8820
- F1: 0.8814
- Precision: 0.8871
- Recall: 0.8820
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.8868 | 1.0 | 69 | 0.4939 | 0.8403 | 0.8376 | 0.8431 | 0.8403 |
| 0.4248 | 2.0 | 138 | 0.3969 | 0.8779 | 0.8768 | 0.8798 | 0.8779 |
| 0.3197 | 3.0 | 207 | 0.4019 | 0.8758 | 0.8757 | 0.8758 | 0.8758 |
| 0.2737 | 4.0 | 276 | 0.3915 | 0.8831 | 0.8827 | 0.8847 | 0.8831 |
| 0.2053 | 5.0 | 345 | 0.4445 | 0.8643 | 0.8650 | 0.8714 | 0.8643 |
| 0.1705 | 6.0 | 414 | 0.4650 | 0.8820 | 0.8814 | 0.8871 | 0.8820 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1