metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_model
results: []
my_awesome_model
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0506
- Accuracy: 0.6959
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: 8e-06
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 383 | 1.6014 | 0.3719 |
| 1.6917 | 2.0 | 766 | 1.1865 | 0.5951 |
| 1.1046 | 3.0 | 1149 | 1.0636 | 0.6473 |
| 0.9029 | 4.0 | 1532 | 1.0561 | 0.6603 |
| 0.9029 | 5.0 | 1915 | 1.0121 | 0.6794 |
| 0.765 | 6.0 | 2298 | 0.9676 | 0.7072 |
| 0.6696 | 7.0 | 2681 | 0.9890 | 0.6985 |
| 0.5756 | 8.0 | 3064 | 1.0216 | 0.7107 |
| 0.5756 | 9.0 | 3447 | 1.0752 | 0.6881 |
| 0.5302 | 10.0 | 3830 | 1.0506 | 0.6959 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1