metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: xlm-ate-nobi-mul-nes
results: []
xlm-ate-nobi-mul-nes
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: 0.7376
- Precision: 0.0
- Recall: 0.0
- F1: 0
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.3037 | 0.45 | 500 | 0.4545 | 0.0 | 0.0 | 0 |
| 0.2008 | 0.91 | 1000 | 0.4427 | 0.0 | 0.0 | 0 |
| 0.1567 | 1.36 | 1500 | 0.5872 | 0.0 | 0.0 | 0 |
| 0.1402 | 1.82 | 2000 | 0.6592 | 0.0 | 0.0 | 0 |
| 0.1218 | 2.27 | 2500 | 0.7135 | 0.0 | 0.0 | 0 |
| 0.1104 | 2.72 | 3000 | 0.7376 | 0.0 | 0.0 | 0 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2