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wikigold_trained_no_DA_small
This model is a fine-tuned version of bert-base-cased on the wikigold_splits dataset. It achieves the following results on the evaluation set:
- Loss: 0.6066
- Precision: 0.3429
- Recall: 0.5455
- F1: 0.4211
- Accuracy: 0.8530
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: 32
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 9 | 0.8525 | 0.0 | 0.0 | 0.0 | 0.7604 |
| No log | 2.0 | 18 | 0.7135 | 0.0 | 0.0 | 0.0 | 0.7604 |
| No log | 3.0 | 27 | 0.5972 | 0.1579 | 0.1364 | 0.1463 | 0.7923 |
| No log | 4.0 | 36 | 0.5108 | 0.0769 | 0.0909 | 0.0833 | 0.8083 |
| No log | 5.0 | 45 | 0.4725 | 0.2333 | 0.3182 | 0.2692 | 0.8466 |
| No log | 6.0 | 54 | 0.4569 | 0.2333 | 0.3182 | 0.2692 | 0.8339 |
| No log | 7.0 | 63 | 0.4428 | 0.2258 | 0.3182 | 0.2642 | 0.8371 |
| No log | 8.0 | 72 | 0.4362 | 0.2121 | 0.3182 | 0.2545 | 0.8435 |
| No log | 9.0 | 81 | 0.4509 | 0.2258 | 0.3182 | 0.2642 | 0.8403 |
| No log | 10.0 | 90 | 0.4614 | 0.2121 | 0.3182 | 0.2545 | 0.8466 |
| No log | 11.0 | 99 | 0.4546 | 0.2188 | 0.3182 | 0.2593 | 0.8435 |
| No log | 12.0 | 108 | 0.4734 | 0.2188 | 0.3182 | 0.2593 | 0.8435 |
| No log | 13.0 | 117 | 0.5098 | 0.2581 | 0.3636 | 0.3019 | 0.8466 |
| No log | 14.0 | 126 | 0.5280 | 0.2258 | 0.3182 | 0.2642 | 0.8435 |
| No log | 15.0 | 135 | 0.5264 | 0.2188 | 0.3182 | 0.2593 | 0.8435 |
| No log | 16.0 | 144 | 0.5317 | 0.2727 | 0.4091 | 0.3273 | 0.8498 |
| No log | 17.0 | 153 | 0.5414 | 0.2581 | 0.3636 | 0.3019 | 0.8466 |
| No log | 18.0 | 162 | 0.5505 | 0.2581 | 0.3636 | 0.3019 | 0.8466 |
| No log | 19.0 | 171 | 0.5521 | 0.2581 | 0.3636 | 0.3019 | 0.8466 |
| No log | 20.0 | 180 | 0.5627 | 0.2581 | 0.3636 | 0.3019 | 0.8466 |
| No log | 21.0 | 189 | 0.5687 | 0.2581 | 0.3636 | 0.3019 | 0.8466 |
| No log | 22.0 | 198 | 0.5751 | 0.2581 | 0.3636 | 0.3019 | 0.8466 |
| No log | 23.0 | 207 | 0.5825 | 0.2727 | 0.4091 | 0.3273 | 0.8498 |
| No log | 24.0 | 216 | 0.5881 | 0.2727 | 0.4091 | 0.3273 | 0.8498 |
| No log | 25.0 | 225 | 0.5930 | 0.2727 | 0.4091 | 0.3273 | 0.8498 |
| No log | 26.0 | 234 | 0.5969 | 0.2727 | 0.4091 | 0.3273 | 0.8498 |
| No log | 27.0 | 243 | 0.5995 | 0.3429 | 0.5455 | 0.4211 | 0.8530 |
| No log | 28.0 | 252 | 0.6017 | 0.3429 | 0.5455 | 0.4211 | 0.8530 |
| No log | 29.0 | 261 | 0.6035 | 0.3429 | 0.5455 | 0.4211 | 0.8530 |
| No log | 30.0 | 270 | 0.6053 | 0.3429 | 0.5455 | 0.4211 | 0.8530 |
| No log | 31.0 | 279 | 0.6063 | 0.3429 | 0.5455 | 0.4211 | 0.8530 |
| No log | 32.0 | 288 | 0.6066 | 0.3429 | 0.5455 | 0.4211 | 0.8530 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.11.6
