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iab_classification-finetuned-mnli-finetuned-mnli
This model is a fine-tuned version of mfreihaut/iab_classification-finetuned-mnli-finetuned-mnli on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8711
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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 250 | 1.5956 |
| 0.9361 | 2.0 | 500 | 0.0409 |
| 0.9361 | 3.0 | 750 | 2.9853 |
| 0.7634 | 4.0 | 1000 | 0.1317 |
| 0.7634 | 5.0 | 1250 | 0.4056 |
| 0.611 | 6.0 | 1500 | 1.8038 |
| 0.611 | 7.0 | 1750 | 0.6305 |
| 0.5627 | 8.0 | 2000 | 0.6923 |
| 0.5627 | 9.0 | 2250 | 3.7410 |
| 0.9863 | 10.0 | 2500 | 2.1912 |
| 0.9863 | 11.0 | 2750 | 1.5405 |
| 1.0197 | 12.0 | 3000 | 1.9271 |
| 1.0197 | 13.0 | 3250 | 1.1741 |
| 0.5186 | 14.0 | 3500 | 1.1864 |
| 0.5186 | 15.0 | 3750 | 0.7945 |
| 0.4042 | 16.0 | 4000 | 1.0645 |
| 0.4042 | 17.0 | 4250 | 1.8826 |
| 0.3637 | 18.0 | 4500 | 0.3234 |
| 0.3637 | 19.0 | 4750 | 0.2641 |
| 0.3464 | 20.0 | 5000 | 0.8596 |
| 0.3464 | 21.0 | 5250 | 0.5601 |
| 0.2449 | 22.0 | 5500 | 0.4543 |
| 0.2449 | 23.0 | 5750 | 1.1986 |
| 0.2595 | 24.0 | 6000 | 0.3642 |
| 0.2595 | 25.0 | 6250 | 1.3606 |
| 0.298 | 26.0 | 6500 | 0.8154 |
| 0.298 | 27.0 | 6750 | 1.1105 |
| 0.1815 | 28.0 | 7000 | 0.7443 |
| 0.1815 | 29.0 | 7250 | 0.2616 |
| 0.165 | 30.0 | 7500 | 0.5318 |
| 0.165 | 31.0 | 7750 | 0.7608 |
| 0.1435 | 32.0 | 8000 | 0.9647 |
| 0.1435 | 33.0 | 8250 | 1.3749 |
| 0.1516 | 34.0 | 8500 | 0.7167 |
| 0.1516 | 35.0 | 8750 | 0.5426 |
| 0.1359 | 36.0 | 9000 | 0.7225 |
| 0.1359 | 37.0 | 9250 | 0.5453 |
| 0.1266 | 38.0 | 9500 | 0.4825 |
| 0.1266 | 39.0 | 9750 | 0.7271 |
| 0.1153 | 40.0 | 10000 | 0.9044 |
| 0.1153 | 41.0 | 10250 | 1.0363 |
| 0.1175 | 42.0 | 10500 | 0.7987 |
| 0.1175 | 43.0 | 10750 | 0.7596 |
| 0.1089 | 44.0 | 11000 | 0.8637 |
| 0.1089 | 45.0 | 11250 | 0.8327 |
| 0.1092 | 46.0 | 11500 | 0.7161 |
| 0.1092 | 47.0 | 11750 | 0.7768 |
| 0.1068 | 48.0 | 12000 | 0.9059 |
| 0.1068 | 49.0 | 12250 | 0.8829 |
| 0.1045 | 50.0 | 12500 | 0.8711 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.10.0
- Datasets 2.5.1
- Tokenizers 0.12.1
