mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_rte
This model is a fine-tuned version of google/mobilebert-uncased on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.5404
- Accuracy: 0.4621
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: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.2735 | 1.0 | 1136 | 0.5753 | 0.4657 |
0.2182 | 2.0 | 2272 | 0.5404 | 0.4621 |
0.2119 | 3.0 | 3408 | 0.5687 | 0.4765 |
0.2089 | 4.0 | 4544 | 0.5697 | 0.4838 |
0.2072 | 5.0 | 5680 | 0.5590 | 0.4801 |
0.2057 | 6.0 | 6816 | 0.5586 | 0.4838 |
0.2047 | 7.0 | 7952 | 0.5556 | 0.4801 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
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