metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: parsi-azma-test3
results: []
parsi-azma-test3
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6884
- F1: 0.5616
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: 5e-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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.3751 | 1.0 | 200 | 0.4398 | 0.5558 |
| 0.4578 | 2.0 | 400 | 0.5175 | 0.5586 |
| 0.3447 | 3.0 | 600 | 0.4170 | 0.5654 |
| 0.3003 | 4.0 | 800 | 0.5484 | 0.5658 |
| 0.2291 | 5.0 | 1000 | 0.6582 | 0.5184 |
| 0.3479 | 6.0 | 1200 | 0.5209 | 0.5591 |
| 0.4688 | 7.0 | 1400 | 0.6091 | 0.5725 |
| 0.1028 | 8.0 | 1600 | 0.6661 | 0.5692 |
| 0.1301 | 9.0 | 1800 | 0.6655 | 0.5636 |
| 0.2515 | 10.0 | 2000 | 0.6884 | 0.5616 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3