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refinement-finetuned-mnli-2
This model is a fine-tuned version of mfreihaut/refinement-finetuned-mnli-1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0242
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 | 303 | 0.3730 |
1.1146 | 2.0 | 606 | 0.9860 |
1.1146 | 3.0 | 909 | 0.7304 |
1.0018 | 4.0 | 1212 | 0.6386 |
1.0045 | 5.0 | 1515 | 0.4228 |
1.0045 | 6.0 | 1818 | 0.6769 |
0.9618 | 7.0 | 2121 | 0.3008 |
0.9618 | 8.0 | 2424 | 0.4496 |
0.964 | 9.0 | 2727 | 0.1826 |
0.9586 | 10.0 | 3030 | 0.0367 |
0.9586 | 11.0 | 3333 | 0.1811 |
1.0467 | 12.0 | 3636 | 0.1352 |
1.0467 | 13.0 | 3939 | 0.0612 |
1.0047 | 14.0 | 4242 | 0.1702 |
1.0012 | 15.0 | 4545 | 0.0622 |
1.0012 | 16.0 | 4848 | 0.7077 |
1.0514 | 17.0 | 5151 | 0.2146 |
1.0514 | 18.0 | 5454 | 0.5531 |
0.9389 | 19.0 | 5757 | 1.2304 |
0.9229 | 20.0 | 6060 | 0.6252 |
0.9229 | 21.0 | 6363 | 0.6844 |
0.9334 | 22.0 | 6666 | 0.5663 |
0.9334 | 23.0 | 6969 | 0.9912 |
0.9312 | 24.0 | 7272 | 0.3112 |
0.8971 | 25.0 | 7575 | 0.4511 |
0.8971 | 26.0 | 7878 | 0.3860 |
0.9022 | 27.0 | 8181 | 0.5904 |
0.9022 | 28.0 | 8484 | 0.4710 |
0.7568 | 29.0 | 8787 | 0.8233 |
0.6753 | 30.0 | 9090 | 0.6951 |
0.6753 | 31.0 | 9393 | 0.6363 |
0.5802 | 32.0 | 9696 | 0.8018 |
0.5802 | 33.0 | 9999 | 0.9381 |
0.5323 | 34.0 | 10302 | 0.9941 |
0.5218 | 35.0 | 10605 | 0.9418 |
0.5218 | 36.0 | 10908 | 0.9236 |
0.4558 | 37.0 | 11211 | 0.4542 |
0.4247 | 38.0 | 11514 | 0.9279 |
0.4247 | 39.0 | 11817 | 0.9567 |
0.43 | 40.0 | 12120 | 0.8077 |
0.43 | 41.0 | 12423 | 0.9595 |
0.352 | 42.0 | 12726 | 0.9189 |
0.3393 | 43.0 | 13029 | 0.8762 |
0.3393 | 44.0 | 13332 | 1.0505 |
0.316 | 45.0 | 13635 | 0.9273 |
0.316 | 46.0 | 13938 | 1.0716 |
0.2983 | 47.0 | 14241 | 1.0084 |
0.2503 | 48.0 | 14544 | 1.1027 |
0.2503 | 49.0 | 14847 | 1.0478 |
0.2462 | 50.0 | 15150 | 1.0242 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.10.0
- Datasets 2.5.1
- Tokenizers 0.12.1