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xlm-roberta-longformer-large-16384
This model is a fine-tuned version of severinsimmler/xlm-roberta-longformer-base-16384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3997
- Precision: 0.0864
- Recall: 0.0667
- F1: 0.0753
- Accuracy: 0.8485
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: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 29 | 0.5927 | 0.0 | 0.0 | 0.0 | 0.7998 |
No log | 2.0 | 58 | 0.4843 | 0.0494 | 0.0059 | 0.0106 | 0.8005 |
No log | 3.0 | 87 | 0.4326 | 0.0348 | 0.0207 | 0.0260 | 0.8286 |
No log | 4.0 | 116 | 0.4310 | 0.0650 | 0.0607 | 0.0628 | 0.8334 |
No log | 5.0 | 145 | 0.3997 | 0.0864 | 0.0667 | 0.0753 | 0.8485 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3