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smashing-sexism-robert-weighted-final-2
This model is a fine-tuned version of readerbench/RoBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.6381
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9887 | 0.1 | 400 | 0.9251 |
| 0.9326 | 0.21 | 800 | 1.0643 |
| 0.8767 | 0.31 | 1200 | 0.8270 |
| 0.9989 | 0.41 | 1600 | 1.0447 |
| 0.8717 | 0.51 | 2000 | 0.8382 |
| 0.8298 | 0.62 | 2400 | 0.8867 |
| 0.9462 | 0.72 | 2800 | 0.8950 |
| 0.8885 | 0.82 | 3200 | 0.8633 |
| 0.9317 | 0.92 | 3600 | 0.8930 |
| 0.7629 | 1.03 | 4000 | 1.1367 |
| 0.7152 | 1.13 | 4400 | 0.9594 |
| 0.66 | 1.23 | 4800 | 0.9411 |
| 0.6867 | 1.33 | 5200 | 1.1500 |
| 0.6281 | 1.44 | 5600 | 0.9684 |
| 0.6442 | 1.54 | 6000 | 1.1268 |
| 0.6769 | 1.64 | 6400 | 0.9762 |
| 0.7184 | 1.74 | 6800 | 0.8957 |
| 0.58 | 1.85 | 7200 | 0.9875 |
| 0.5751 | 1.95 | 7600 | 1.2363 |
| 0.4031 | 2.05 | 8000 | 1.3173 |
| 0.3862 | 2.15 | 8400 | 1.3331 |
| 0.5009 | 2.26 | 8800 | 1.4265 |
| 0.4591 | 2.36 | 9200 | 1.5329 |
| 0.4284 | 2.46 | 9600 | 1.3033 |
| 0.5236 | 2.56 | 10000 | 1.2444 |
| 0.5135 | 2.67 | 10400 | 1.2472 |
| 0.5369 | 2.77 | 10800 | 1.6505 |
| 0.4701 | 2.87 | 11200 | 1.3840 |
| 0.5371 | 2.97 | 11600 | 1.3600 |
| 0.2557 | 3.08 | 12000 | 1.4148 |
| 0.2952 | 3.18 | 12400 | 1.7975 |
| 0.2098 | 3.28 | 12800 | 2.0480 |
| 0.236 | 3.38 | 13200 | 1.9231 |
| 0.2414 | 3.49 | 13600 | 1.6038 |
| 0.387 | 3.59 | 14000 | 1.6627 |
| 0.3059 | 3.69 | 14400 | 1.5931 |
| 0.2872 | 3.79 | 14800 | 1.5828 |
| 0.1751 | 3.9 | 15200 | 1.9071 |
| 0.2429 | 4.0 | 15600 | 1.6990 |
| 0.164 | 4.1 | 16000 | 1.9178 |
| 0.0941 | 4.2 | 16400 | 2.1213 |
| 0.1948 | 4.31 | 16800 | 2.0160 |
| 0.1442 | 4.41 | 17200 | 2.0305 |
| 0.2209 | 4.51 | 17600 | 1.9717 |
| 0.1375 | 4.61 | 18000 | 2.0309 |
| 0.1995 | 4.72 | 18400 | 2.0615 |
| 0.1421 | 4.82 | 18800 | 2.0320 |
| 0.2076 | 4.92 | 19200 | 1.9974 |
| 0.0748 | 5.02 | 19600 | 1.9942 |
| 0.0689 | 5.13 | 20000 | 2.1029 |
| 0.0841 | 5.23 | 20400 | 2.2356 |
| 0.0782 | 5.33 | 20800 | 2.2074 |
| 0.1662 | 5.43 | 21200 | 2.3315 |
| 0.0415 | 5.54 | 21600 | 2.5986 |
| 0.0731 | 5.64 | 22000 | 2.2913 |
| 0.0851 | 5.74 | 22400 | 2.4306 |
| 0.0923 | 5.84 | 22800 | 2.4737 |
| 0.099 | 5.95 | 23200 | 2.2077 |
| 0.0297 | 6.05 | 23600 | 2.2406 |
| 0.0365 | 6.15 | 24000 | 2.5536 |
| 0.0131 | 6.25 | 24400 | 2.7311 |
| 0.0838 | 6.36 | 24800 | 2.3021 |
| 0.0392 | 6.46 | 25200 | 2.4769 |
| 0.0357 | 6.56 | 25600 | 2.4404 |
| 0.0955 | 6.66 | 26000 | 2.4813 |
| 0.1119 | 6.77 | 26400 | 2.3819 |
| 0.0916 | 6.87 | 26800 | 2.5341 |
| 0.1437 | 6.97 | 27200 | 2.2940 |
| 0.0333 | 7.08 | 27600 | 2.4652 |
| 0.0276 | 7.18 | 28000 | 2.5684 |
| 0.0306 | 7.28 | 28400 | 2.4722 |
| 0.0248 | 7.38 | 28800 | 2.7375 |
| 0.0199 | 7.49 | 29200 | 2.7708 |
| 0.0443 | 7.59 | 29600 | 2.7067 |
| 0.0119 | 7.69 | 30000 | 2.6394 |
| 0.0606 | 7.79 | 30400 | 2.5045 |
| 0.0467 | 7.9 | 30800 | 2.3479 |
| 0.0438 | 8.0 | 31200 | 2.7489 |
| 0.0033 | 8.1 | 31600 | 2.6423 |
| 0.0306 | 8.2 | 32000 | 2.5070 |
| 0.033 | 8.31 | 32400 | 2.7068 |
| 0.0114 | 8.41 | 32800 | 2.7400 |
| 0.0032 | 8.51 | 33200 | 2.5803 |
| 0.0305 | 8.61 | 33600 | 2.8058 |
| 0.0253 | 8.72 | 34000 | 2.5497 |
| 0.0183 | 8.82 | 34400 | 2.5782 |
| 0.0651 | 8.92 | 34800 | 2.7173 |
| 0.0345 | 9.02 | 35200 | 2.5939 |
| 0.0206 | 9.13 | 35600 | 2.6243 |
| 0.0018 | 9.23 | 36000 | 2.5503 |
| 0.0484 | 9.33 | 36400 | 2.7006 |
| 0.0359 | 9.43 | 36800 | 2.6202 |
| 0.006 | 9.54 | 37200 | 2.6260 |
| 0.0205 | 9.64 | 37600 | 2.7143 |
| 0.0153 | 9.74 | 38000 | 2.6923 |
| 0.0342 | 9.84 | 38400 | 2.6475 |
| 0.011 | 9.95 | 38800 | 2.6381 |
Framework versions
- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
