metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: xlm-roberta-base
model-index:
- name: sentiment-10Epochs-2-work-please
results: []
sentiment-10Epochs-2-work-please
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: 0.7450
- Accuracy: 0.8549
- F1: 0.8516
- Precision: 0.8714
- Recall: 0.8327
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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.3685 | 1.0 | 7088 | 0.4334 | 0.8590 | 0.8463 | 0.9304 | 0.7762 |
| 0.3721 | 2.0 | 14176 | 0.3822 | 0.8673 | 0.8575 | 0.9257 | 0.7987 |
| 0.3393 | 3.0 | 21264 | 0.4634 | 0.8705 | 0.8619 | 0.9228 | 0.8086 |
| 0.3017 | 4.0 | 28352 | 0.4806 | 0.8708 | 0.8630 | 0.9186 | 0.8137 |
| 0.3072 | 5.0 | 35440 | 0.4509 | 0.87 | 0.8648 | 0.9009 | 0.8314 |
| 0.2833 | 6.0 | 42528 | 0.5339 | 0.8627 | 0.8581 | 0.8879 | 0.8302 |
| 0.2633 | 7.0 | 49616 | 0.5457 | 0.8637 | 0.8614 | 0.8759 | 0.8473 |
| 0.2418 | 8.0 | 56704 | 0.6408 | 0.8589 | 0.8563 | 0.8722 | 0.8410 |
| 0.1999 | 9.0 | 63792 | 0.7404 | 0.8530 | 0.8485 | 0.8752 | 0.8235 |
| 0.1809 | 10.0 | 70880 | 0.7450 | 0.8549 | 0.8516 | 0.8714 | 0.8327 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0
- Datasets 2.0.0
- Tokenizers 0.11.6