<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
mobilebert_sa_GLUE_Experiment_logit_kd_mnli
This model is a fine-tuned version of google/mobilebert-uncased on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 1.1966
- Accuracy: 0.6173
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 |
---|---|---|---|---|
1.6232 | 1.0 | 3068 | 1.3870 | 0.5505 |
1.4341 | 2.0 | 6136 | 1.3186 | 0.5834 |
1.3724 | 3.0 | 9204 | 1.2819 | 0.5943 |
1.3249 | 4.0 | 12272 | 1.2702 | 0.5982 |
1.2788 | 5.0 | 15340 | 1.2359 | 0.6031 |
1.2302 | 6.0 | 18408 | 1.2008 | 0.6193 |
1.1842 | 7.0 | 21476 | 1.1991 | 0.6222 |
1.1441 | 8.0 | 24544 | 1.1839 | 0.6202 |
1.1057 | 9.0 | 27612 | 1.1861 | 0.6244 |
1.0715 | 10.0 | 30680 | 1.1755 | 0.6250 |
1.0386 | 11.0 | 33748 | 1.1972 | 0.6313 |
1.0066 | 12.0 | 36816 | 1.2149 | 0.6276 |
0.9767 | 13.0 | 39884 | 1.2187 | 0.6193 |
0.9482 | 14.0 | 42952 | 1.2004 | 0.6226 |
0.921 | 15.0 | 46020 | 1.2093 | 0.6194 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2