tinybert_train_book_v2_qqp
This model is a fine-tuned version of gokulsrinivasagan/tinybert_train_book_v2 on the GLUE QQP dataset. It achieves the following results on the evaluation set:
- Loss: 0.2906
- Accuracy: 0.8763
- F1: 0.8292
- Combined Score: 0.8528
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
---|---|---|---|---|---|---|
0.397 | 1.0 | 1422 | 0.3445 | 0.8484 | 0.7789 | 0.8137 |
0.2958 | 2.0 | 2844 | 0.3029 | 0.8695 | 0.8221 | 0.8458 |
0.2432 | 3.0 | 4266 | 0.2906 | 0.8763 | 0.8292 | 0.8528 |
0.1995 | 4.0 | 5688 | 0.2984 | 0.8798 | 0.8315 | 0.8557 |
0.1629 | 5.0 | 7110 | 0.3093 | 0.8847 | 0.8454 | 0.8651 |
0.1334 | 6.0 | 8532 | 0.3454 | 0.8849 | 0.8435 | 0.8642 |
0.1097 | 7.0 | 9954 | 0.3595 | 0.8847 | 0.8452 | 0.8649 |
0.0925 | 8.0 | 11376 | 0.3933 | 0.8854 | 0.8441 | 0.8647 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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Model tree for gokulsrinivasagan/tinybert_train_book_v2_qqp
Base model
distilbert/distilbert-base-uncased
Finetuned
gokulsrinivasagan/tinybert_train_book_v2
Dataset used to train gokulsrinivasagan/tinybert_train_book_v2_qqp
Evaluation results
- Accuracy on GLUE QQPself-reported0.876
- F1 on GLUE QQPself-reported0.829