metadata
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: xlm-roberta-base
metrics:
- accuracy
- f1
model-index:
- name: loha_fine_tuned_cb_XLMroberta
results: []
loha_fine_tuned_cb_XLMroberta
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: 1.3380
- Accuracy: 0.3182
- F1: 0.1536
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
- training_steps: 400
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8809 | 3.5714 | 50 | 1.2255 | 0.3182 | 0.1536 |
| 0.7544 | 7.1429 | 100 | 1.2817 | 0.3182 | 0.1536 |
| 0.7672 | 10.7143 | 150 | 1.3164 | 0.3182 | 0.1536 |
| 0.7357 | 14.2857 | 200 | 1.3296 | 0.3182 | 0.1536 |
| 0.7661 | 17.8571 | 250 | 1.3282 | 0.3182 | 0.1536 |
| 0.7522 | 21.4286 | 300 | 1.3353 | 0.3182 | 0.1536 |
| 0.7208 | 25.0 | 350 | 1.3379 | 0.3182 | 0.1536 |
| 0.7377 | 28.5714 | 400 | 1.3380 | 0.3182 | 0.1536 |
Framework versions
- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1