router-mmBERT-small-text-only-v3
This model is a fine-tuned version of jhu-clsp/mmBERT-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5264
- Accuracy: 0.7443
- Precision: 0.7422
- Recall: 0.7443
- F1: 0.7282
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 1.5114 | 0.4432 | 0.4804 | 0.4432 | 0.4537 |
| 0.7931 | 0.2273 | 20 | 0.9312 | 0.6648 | 0.6848 | 0.6648 | 0.5784 |
| 0.7752 | 0.4545 | 40 | 0.9223 | 0.4886 | 0.7377 | 0.4886 | 0.4320 |
| 0.5251 | 0.6818 | 60 | 0.5346 | 0.6989 | 0.6940 | 0.6989 | 0.6659 |
| 0.5975 | 0.9091 | 80 | 0.5975 | 0.6534 | 0.7276 | 0.6534 | 0.6573 |
| 0.551 | 1.1364 | 100 | 0.5680 | 0.7273 | 0.7225 | 0.7273 | 0.7090 |
| 0.5093 | 1.3636 | 120 | 0.5872 | 0.7045 | 0.6952 | 0.7045 | 0.6951 |
| 0.5315 | 1.5909 | 140 | 0.5398 | 0.75 | 0.7593 | 0.75 | 0.7265 |
| 0.5231 | 1.8182 | 160 | 0.5264 | 0.7443 | 0.7422 | 0.7443 | 0.7282 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1