metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_cb_XLMroberta
results: []
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: 1.4876
- Accuracy: 0.6364
- F1: 0.5977
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 |
|---|---|---|---|---|---|
| 0.8279 | 3.5714 | 50 | 1.1428 | 0.3182 | 0.1536 |
| 0.6981 | 7.1429 | 100 | 1.2578 | 0.3182 | 0.1536 |
| 0.6005 | 10.7143 | 150 | 1.2018 | 0.3636 | 0.2430 |
| 0.2959 | 14.2857 | 200 | 1.1990 | 0.6364 | 0.5916 |
| 0.1743 | 17.8571 | 250 | 1.5253 | 0.5909 | 0.5562 |
| 0.1206 | 21.4286 | 300 | 1.8099 | 0.5 | 0.4423 |
| 0.0357 | 25.0 | 350 | 1.7105 | 0.5909 | 0.5545 |
| 0.0189 | 28.5714 | 400 | 1.4876 | 0.6364 | 0.5977 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1