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mobilebert_sa_GLUE_Experiment_logit_kd_mnli_256
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: 1.2282
- Accuracy: 0.6120
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 |
|---|---|---|---|---|
| 1.6433 | 1.0 | 3068 | 1.4078 | 0.5457 |
| 1.4683 | 2.0 | 6136 | 1.3590 | 0.5658 |
| 1.4077 | 3.0 | 9204 | 1.3106 | 0.5772 |
| 1.3591 | 4.0 | 12272 | 1.2971 | 0.5904 |
| 1.3213 | 5.0 | 15340 | 1.2764 | 0.5957 |
| 1.2849 | 6.0 | 18408 | 1.2562 | 0.6029 |
| 1.2475 | 7.0 | 21476 | 1.2524 | 0.6038 |
| 1.2073 | 8.0 | 24544 | 1.2384 | 0.6066 |
| 1.1713 | 9.0 | 27612 | 1.2377 | 0.6109 |
| 1.1371 | 10.0 | 30680 | 1.2228 | 0.6077 |
| 1.1069 | 11.0 | 33748 | 1.2126 | 0.6196 |
| 1.0775 | 12.0 | 36816 | 1.2232 | 0.6271 |
| 1.0491 | 13.0 | 39884 | 1.2440 | 0.6110 |
| 1.0228 | 14.0 | 42952 | 1.2741 | 0.6079 |
| 0.9977 | 15.0 | 46020 | 1.2448 | 0.6158 |
| 0.974 | 16.0 | 49088 | 1.3261 | 0.6206 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
