gmra_model_distilbert-base-uncased-distilled-squad_07112024T110436
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: 0.3023
- Accuracy: 94.1125
- F1: 0.9587
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 0.9982 | 142 | 0.3683 | 88.0492 | 0.7519 |
No log | 1.9965 | 284 | 0.2634 | 91.5641 | 0.9238 |
No log | 2.9947 | 426 | 0.2386 | 92.8822 | 0.9432 |
0.3507 | 4.0 | 569 | 0.2321 | 93.9367 | 0.9579 |
0.3507 | 4.9982 | 711 | 0.2897 | 93.4095 | 0.9536 |
0.3507 | 5.9965 | 853 | 0.2745 | 94.2882 | 0.9606 |
0.3507 | 6.9947 | 995 | 0.2892 | 94.3761 | 0.9616 |
0.0379 | 8.0 | 1138 | 0.3055 | 94.0246 | 0.9579 |
0.0379 | 8.9982 | 1280 | 0.3144 | 93.7610 | 0.9562 |
0.0379 | 9.9824 | 1420 | 0.3023 | 94.1125 | 0.9587 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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