metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: sentiment-10Epochs
results: []
sentiment-10Epochs
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: 0.7030
- Accuracy: 0.8603
- F1: 0.8585
- Precision: 0.8699
- Recall: 0.8473
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 |
|---|---|---|---|---|---|---|---|
| 0.3645 | 1.0 | 7088 | 0.4315 | 0.8603 | 0.8466 | 0.9386 | 0.7711 |
| 0.374 | 2.0 | 14176 | 0.4015 | 0.8713 | 0.8648 | 0.9105 | 0.8235 |
| 0.3363 | 3.0 | 21264 | 0.4772 | 0.8705 | 0.8615 | 0.9256 | 0.8057 |
| 0.3131 | 4.0 | 28352 | 0.4579 | 0.8702 | 0.8650 | 0.9007 | 0.8321 |
| 0.3097 | 5.0 | 35440 | 0.4160 | 0.8721 | 0.8663 | 0.9069 | 0.8292 |
| 0.2921 | 6.0 | 42528 | 0.4638 | 0.8673 | 0.8630 | 0.8917 | 0.8362 |
| 0.2725 | 7.0 | 49616 | 0.5183 | 0.8654 | 0.8602 | 0.8947 | 0.8283 |
| 0.2481 | 8.0 | 56704 | 0.5846 | 0.8649 | 0.8624 | 0.8787 | 0.8467 |
| 0.192 | 9.0 | 63792 | 0.6481 | 0.8610 | 0.8596 | 0.8680 | 0.8514 |
| 0.1945 | 10.0 | 70880 | 0.7030 | 0.8603 | 0.8585 | 0.8699 | 0.8473 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0
- Datasets 2.0.0
- Tokenizers 0.11.6