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ikitracs_conditional
This model is a fine-tuned version of sentence-transformers/all-mpnet-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9018
- Precision Weighted: 0.7669
- Precision Macro: 0.7479
- Recall Weighted: 0.7712
- Recall Samples: 0.7345
- F1-score: 0.7400
- Accuracy: 0.7712
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: 5.8e-05
- train_batch_size: 8
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision Weighted | Precision Macro | Recall Weighted | Recall Samples | F1-score | Accuracy |
|---|---|---|---|---|---|---|---|---|---|
| 0.6787 | 1.0 | 212 | 0.6461 | 0.6859 | 0.6493 | 0.6792 | 0.6546 | 0.6513 | 0.6792 |
| 0.6006 | 2.0 | 424 | 0.6125 | 0.7370 | 0.7301 | 0.7429 | 0.6690 | 0.6792 | 0.7429 |
| 0.4826 | 3.0 | 636 | 0.7111 | 0.7458 | 0.7270 | 0.7524 | 0.7071 | 0.7142 | 0.7524 |
| 0.3487 | 4.0 | 848 | 0.7359 | 0.7536 | 0.7242 | 0.75 | 0.7297 | 0.7266 | 0.75 |
| 0.2199 | 5.0 | 1060 | 0.9018 | 0.7669 | 0.7479 | 0.7712 | 0.7345 | 0.7400 | 0.7712 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
