metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 20230928-10-xlm-roberta-base-new
results: []
20230928-10-xlm-roberta-base-new
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.4847
- Loss: nan
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 4.5116 | 0.46 | 200 | 0.2970 | nan |
| 3.9887 | 0.91 | 400 | 0.3086 | 4.0522 |
| 3.9101 | 1.37 | 600 | 0.3138 | nan |
| 3.7634 | 1.82 | 800 | 0.3184 | 3.7682 |
| 3.4413 | 2.28 | 1000 | 0.3977 | 2.9317 |
| 3.4478 | 2.73 | 1200 | 0.4102 | nan |
| 3.4179 | 3.19 | 1400 | 0.3790 | 3.2163 |
| 3.2165 | 3.64 | 1600 | 0.4435 | 2.7062 |
| 3.1388 | 4.1 | 1800 | 0.4540 | 2.8629 |
| 3.0987 | 4.56 | 2000 | 0.4509 | nan |
| 3.0614 | 5.01 | 2200 | 0.4894 | nan |
| 3.1399 | 5.47 | 2400 | 0.5337 | nan |
| 3.0387 | 5.92 | 2600 | 0.4667 | 3.0331 |
| 2.9728 | 6.38 | 2800 | 0.4571 | nan |
| 2.9138 | 6.83 | 3000 | 0.4306 | 2.8179 |
| 2.9157 | 7.29 | 3200 | 0.4520 | nan |
| 2.8103 | 7.74 | 3400 | 0.5 | nan |
| 2.7693 | 8.2 | 3600 | 0.4841 | 2.9349 |
| 2.8204 | 8.66 | 3800 | 0.4727 | 2.7438 |
| 2.7711 | 9.11 | 4000 | 0.5123 | 2.6654 |
| 2.7196 | 9.57 | 4200 | 0.4847 | nan |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3