This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

accuracy

f1

: 0.5561

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The following hyperparameters were used during training:

| Training Loss | Epoch | Step | Validation Loss |

accuracy

|

f1

| |:-------------:|:-----:|:----:|:---------------:|:------------:|:------:| | No log | 1.0 | 122 | 5.7744 | 0.4178 | 0.3923 | | No log | 2.0 | 244 | 5.0403 | 0.4272 | 0.4213 | | No log | 3.0 | 366 | 4.5657 | 0.4977 | 0.4720 | | No log | 4.0 | 488 | 4.3136 | 0.4789 | 0.4495 | | 5.0225 | 5.0 | 610 | 3.9342 | 0.5399 | 0.5222 | | 5.0225 | 6.0 | 732 | 3.7035 | 0.5446 | 0.5357 | | 5.0225 | 7.0 | 854 | 3.6549 | 0.5399 | 0.5230 | | 5.0225 | 8.0 | 976 | 3.4910 | 0.5352 | 0.5140 | | 3.4198 | 9.0 | 1098 | 3.5480 | 0.5305 | 0.5135 | | 3.4198 | 10.0 | 1220 | 3.3192 | 0.5352 | 0.5263 | | 3.4198 | 11.0 | 1342 | 3.2132 | 0.5305 | 0.5235 | | 3.4198 | 12.0 | 1464 | 3.1579 | 0.5634 | 0.5468 | | 2.3583 | 13.0 | 1586 | 3.1269 | 0.5634 | 0.5575 | | 2.3583 | 14.0 | 1708 | 3.1811 | 0.5540 | 0.5359 | | 2.3583 | 15.0 | 1830 | 3.0422 | 0.5634 | 0.5523 | | 2.3583 | 16.0 | 1952 | 2.9863 | 0.5728 | 0.5630 | | 1.6426 | 17.0 | 2074 | 2.9256 | 0.5634 | 0.5527 | | 1.6426 | 18.0 | 2196 | 2.8626 | 0.5728 | 0.5561 | | 1.6426 | 19.0 | 2318 | 2.9229 | 0.5587 | 0.5423 | | 1.6426 | 20.0 | 2440 | 2.9497 | 0.5775 | 0.5625 |