<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
bert-25
This model is a fine-tuned version of deepset/bert-base-cased-squad2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 10.9150
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|
| 11.2284 | 0.18 | 5 | 12.3262 |
| 10.9876 | 0.36 | 10 | 12.2748 |
| 11.1442 | 0.54 | 15 | 12.2245 |
| 10.9113 | 0.71 | 20 | 12.1755 |
| 10.8104 | 0.89 | 25 | 12.1267 |
| 10.6362 | 1.07 | 30 | 12.0793 |
| 10.8187 | 1.25 | 35 | 12.0330 |
| 10.7052 | 1.43 | 40 | 11.9875 |
| 10.6594 | 1.61 | 45 | 11.9432 |
| 10.6863 | 1.79 | 50 | 11.8997 |
| 10.7858 | 1.96 | 55 | 11.8569 |
| 10.626 | 2.14 | 60 | 11.8158 |
| 10.4246 | 2.32 | 65 | 11.7756 |
| 10.3939 | 2.5 | 70 | 11.7359 |
| 10.7641 | 2.68 | 75 | 11.6970 |
| 10.341 | 2.86 | 80 | 11.6597 |
| 10.3492 | 3.04 | 85 | 11.6228 |
| 10.797 | 3.21 | 90 | 11.5867 |
| 10.3496 | 3.39 | 95 | 11.5514 |
| 10.1967 | 3.57 | 100 | 11.5177 |
| 10.4702 | 3.75 | 105 | 11.4843 |
| 10.3715 | 3.93 | 110 | 11.4521 |
| 10.1039 | 4.11 | 115 | 11.4213 |
| 10.1126 | 4.29 | 120 | 11.3915 |
| 9.9939 | 4.46 | 125 | 11.3625 |
| 10.1773 | 4.64 | 130 | 11.3342 |
| 10.062 | 4.82 | 135 | 11.3068 |
| 10.2641 | 5.0 | 140 | 11.2806 |
| 10.2323 | 5.18 | 145 | 11.2554 |
| 10.037 | 5.36 | 150 | 11.2309 |
| 10.0938 | 5.54 | 155 | 11.2069 |
| 9.8816 | 5.71 | 160 | 11.1845 |
| 10.124 | 5.89 | 165 | 11.1625 |
| 9.873 | 6.07 | 170 | 11.1416 |
| 9.7348 | 6.25 | 175 | 11.1220 |
| 9.9028 | 6.43 | 180 | 11.1028 |
| 9.997 | 6.61 | 185 | 11.0846 |
| 9.9333 | 6.79 | 190 | 11.0676 |
| 9.9954 | 6.96 | 195 | 11.0511 |
| 10.311 | 7.14 | 200 | 11.0356 |
| 9.7617 | 7.32 | 205 | 11.0213 |
| 10.0068 | 7.5 | 210 | 11.0075 |
| 9.6182 | 7.68 | 215 | 10.9949 |
| 9.7642 | 7.86 | 220 | 10.9835 |
| 9.8524 | 8.04 | 225 | 10.9728 |
| 9.7615 | 8.21 | 230 | 10.9630 |
| 9.7559 | 8.39 | 235 | 10.9542 |
| 9.5819 | 8.57 | 240 | 10.9461 |
| 9.5843 | 8.75 | 245 | 10.9392 |
| 10.05 | 8.93 | 250 | 10.9331 |
| 10.0722 | 9.11 | 255 | 10.9276 |
| 9.665 | 9.29 | 260 | 10.9233 |
| 9.7631 | 9.46 | 265 | 10.9197 |
| 9.7963 | 9.64 | 270 | 10.9172 |
| 9.9692 | 9.82 | 275 | 10.9155 |
| 9.885 | 10.0 | 280 | 10.9150 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
