metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_roberta-base
results: []
finetuned_roberta-base
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: 1.2574
- Accuracy: 0.6033
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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.48 | 1.0 | 75 | 1.4001 | 0.41 |
| 1.2847 | 2.0 | 150 | 1.1993 | 0.58 |
| 1.1522 | 3.0 | 225 | 1.0007 | 0.6333 |
| 0.9921 | 4.0 | 300 | 0.9189 | 0.66 |
| 0.9104 | 5.0 | 375 | 0.8855 | 0.69 |
| 0.8371 | 6.0 | 450 | 0.9431 | 0.6767 |
| 0.699 | 7.0 | 525 | 0.9500 | 0.6633 |
| 0.6872 | 8.0 | 600 | 0.9728 | 0.7033 |
| 0.5867 | 9.0 | 675 | 0.9939 | 0.6867 |
| 0.5323 | 10.0 | 750 | 1.1115 | 0.69 |
| 0.4066 | 11.0 | 825 | 1.2031 | 0.6667 |
| 0.3517 | 12.0 | 900 | 1.2193 | 0.65 |
| 0.3114 | 13.0 | 975 | 1.2281 | 0.67 |
| 0.3102 | 14.0 | 1050 | 1.2691 | 0.67 |
| 0.2681 | 15.0 | 1125 | 1.2818 | 0.6633 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1