fm-tc-concat-multi
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2453
- Accuracy: 0.96
- Precision: 0.9606
- Recall: 0.9600
- F1: 0.9593
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: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.7009 | 1.0 | 1125 | 0.5866 | 0.852 | 0.8866 | 0.8520 | 0.8521 |
| 0.519 | 2.0 | 2250 | 0.3544 | 0.926 | 0.9308 | 0.9260 | 0.9252 |
| 0.2278 | 3.0 | 3375 | 0.2723 | 0.936 | 0.9384 | 0.9360 | 0.9355 |
| 0.0705 | 4.0 | 4500 | 0.2528 | 0.962 | 0.9629 | 0.9620 | 0.9613 |
| 0.0312 | 5.0 | 5625 | 0.2453 | 0.96 | 0.9606 | 0.9600 | 0.9593 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for adriansanz/fm-tc-concat-multi
Base model
FacebookAI/xlm-roberta-base