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bert-base-uncased-yahoo_answers_topics
This model is a fine-tuned version of bert-base-uncased on the yahoo_answers_topics dataset. It achieves the following results on the evaluation set:
- Loss: 0.8092
- Accuracy: 0.7499
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 86625
- training_steps: 866250
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.162 | 0.01 | 2000 | 1.7444 | 0.5681 |
| 1.3126 | 0.02 | 4000 | 1.0081 | 0.7054 |
| 0.9592 | 0.03 | 6000 | 0.9021 | 0.7234 |
| 0.8903 | 0.05 | 8000 | 0.8827 | 0.7276 |
| 0.8685 | 0.06 | 10000 | 0.8540 | 0.7341 |
| 0.8422 | 0.07 | 12000 | 0.8547 | 0.7365 |
| 0.8535 | 0.08 | 14000 | 0.8264 | 0.7372 |
| 0.8178 | 0.09 | 16000 | 0.8331 | 0.7389 |
| 0.8325 | 0.1 | 18000 | 0.8242 | 0.7411 |
| 0.8181 | 0.12 | 20000 | 0.8356 | 0.7437 |
| 0.8171 | 0.13 | 22000 | 0.8090 | 0.7451 |
| 0.8092 | 0.14 | 24000 | 0.8469 | 0.7392 |
| 0.8057 | 0.15 | 26000 | 0.8185 | 0.7478 |
| 0.8085 | 0.16 | 28000 | 0.8090 | 0.7467 |
| 0.8229 | 0.17 | 30000 | 0.8225 | 0.7417 |
| 0.8151 | 0.18 | 32000 | 0.8262 | 0.7419 |
| 0.81 | 0.2 | 34000 | 0.8149 | 0.7383 |
| 0.8073 | 0.21 | 36000 | 0.8225 | 0.7441 |
| 0.816 | 0.22 | 38000 | 0.8037 | 0.744 |
| 0.8217 | 0.23 | 40000 | 0.8409 | 0.743 |
| 0.82 | 0.24 | 42000 | 0.8286 | 0.7385 |
| 0.8101 | 0.25 | 44000 | 0.8282 | 0.7413 |
| 0.8254 | 0.27 | 46000 | 0.8170 | 0.7414 |
Framework versions
- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.6.1
- Tokenizers 0.10.3
