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gmra_model_distilbert-base-uncased-distilled-squad_17082023T151553
This model is a fine-tuned version of distilbert-base-uncased-distilled-squad on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4453
- Accuracy: 93.84885764499121%
- F1: 0.9505
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 284 | 0.3755 | 87.5219683655536% | 0.8548 |
| 0.462 | 2.0 | 568 | 0.2464 | 92.1792618629174% | 0.9384 |
| 0.462 | 3.0 | 852 | 0.3129 | 92.88224956063269% | 0.9402 |
| 0.1115 | 4.0 | 1137 | 0.3364 | 93.23374340949033% | 0.9492 |
| 0.1115 | 5.0 | 1421 | 0.3840 | 93.58523725834797% | 0.9531 |
| 0.0445 | 6.0 | 1705 | 0.4202 | 93.93673110720563% | 0.9514 |
| 0.0445 | 7.0 | 1989 | 0.4128 | 93.7609841827768% | 0.9538 |
| 0.0176 | 8.0 | 2274 | 0.4336 | 93.84885764499121% | 0.9544 |
| 0.0084 | 9.0 | 2558 | 0.4445 | 93.7609841827768% | 0.9538 |
| 0.0084 | 9.99 | 2840 | 0.4453 | 93.84885764499121% | 0.9505 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.2
