metadata
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlm-roberta-large_latest_Nov2023
results: []
xlm-roberta-large_latest_Nov2023
This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3474
- Accuracy: 0.7735
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6171 | 0.2 | 100 | 0.5548 | 0.569 |
| 0.5233 | 0.4 | 200 | 0.4284 | 0.715 |
| 0.4572 | 0.6 | 300 | 0.4136 | 0.7185 |
| 0.4347 | 0.8 | 400 | 0.4087 | 0.7065 |
| 0.4379 | 1.0 | 500 | 0.4107 | 0.7275 |
| 0.4285 | 1.2 | 600 | 0.4007 | 0.7285 |
| 0.3897 | 1.4 | 700 | 0.3986 | 0.7315 |
| 0.3862 | 1.6 | 800 | 0.3536 | 0.76 |
| 0.3575 | 1.8 | 900 | 0.3506 | 0.762 |
| 0.3247 | 2.0 | 1000 | 0.3474 | 0.7735 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1