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roberta-finetuned-WebClassification-v2-smalllinguaENES
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: 1.0053
- Accuracy: 0.9355
- F1: 0.9355
- Precision: 0.9355
- Recall: 0.9355
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 16 | 2.4058 | 0.1613 | 0.1613 | 0.1613 | 0.1613 |
| No log | 2.0 | 32 | 2.3931 | 0.0968 | 0.0968 | 0.0968 | 0.0968 |
| No log | 3.0 | 48 | 1.9594 | 0.4516 | 0.4516 | 0.4516 | 0.4516 |
| No log | 4.0 | 64 | 1.7428 | 0.6129 | 0.6129 | 0.6129 | 0.6129 |
| No log | 5.0 | 80 | 1.3781 | 0.8387 | 0.8387 | 0.8387 | 0.8387 |
| No log | 6.0 | 96 | 1.0053 | 0.9355 | 0.9355 | 0.9355 | 0.9355 |
| No log | 7.0 | 112 | 0.8489 | 0.8387 | 0.8387 | 0.8387 | 0.8387 |
| No log | 8.0 | 128 | 0.7135 | 0.8710 | 0.8710 | 0.8710 | 0.8710 |
| No log | 9.0 | 144 | 0.6700 | 0.8710 | 0.8710 | 0.8710 | 0.8710 |
| No log | 10.0 | 160 | 0.6511 | 0.9355 | 0.9355 | 0.9355 | 0.9355 |
Framework versions
- Transformers 4.27.3
- Pytorch 2.0.0+cpu
- Datasets 2.10.1
- Tokenizers 0.13.2
