xlm-roberta-base-finetuned-removed-0530
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: 0.9944
- Accuracy: 0.8717
- F1: 0.8719
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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 3180 | 0.6390 | 0.7899 | 0.7852 |
| No log | 2.0 | 6360 | 0.5597 | 0.8223 | 0.8230 |
| No log | 3.0 | 9540 | 0.5177 | 0.8462 | 0.8471 |
| No log | 4.0 | 12720 | 0.5813 | 0.8642 | 0.8647 |
| No log | 5.0 | 15900 | 0.7324 | 0.8557 | 0.8568 |
| No log | 6.0 | 19080 | 0.7589 | 0.8626 | 0.8634 |
| No log | 7.0 | 22260 | 0.7958 | 0.8752 | 0.8751 |
| 0.3923 | 8.0 | 25440 | 0.9177 | 0.8651 | 0.8653 |
| 0.3923 | 9.0 | 28620 | 1.0188 | 0.8673 | 0.8671 |
| 0.3923 | 10.0 | 31800 | 0.9944 | 0.8717 | 0.8719 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1