metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: best-model-v1
results: []
best-model-v1
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6069
- Accuracy: 0.4410
- Precision: 0.5118
- Recall: 0.6489
- F1 Score: 0.5711
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|---|---|---|---|---|---|---|---|
| 1.7357 | 0.3911 | 500 | 0.8218 | 0.3192 | 0.2798 | 0.2506 | 0.2551 |
| 1.5848 | 0.7822 | 1000 | 0.7275 | 0.3937 | 0.4789 | 0.4157 | 0.4387 |
| 1.398 | 1.1729 | 1500 | 0.6628 | 0.4123 | 0.4885 | 0.5846 | 0.5251 |
| 1.2999 | 1.5639 | 2000 | 0.6264 | 0.4295 | 0.5046 | 0.6402 | 0.5626 |
| 1.2964 | 1.9550 | 2500 | 0.6101 | 0.4260 | 0.4991 | 0.6553 | 0.5655 |
| 1.2479 | 2.3457 | 3000 | 0.6069 | 0.4381 | 0.5082 | 0.6506 | 0.5695 |
| 1.267 | 2.7368 | 3500 | 0.6069 | 0.4410 | 0.5118 | 0.6489 | 0.5711 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0