mobilebert_add_GLUE_Experiment_logit_kd_mrpc_256
This model is a fine-tuned version of google/mobilebert-uncased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.5536
- Accuracy: 0.6838
- F1: 0.8122
- Combined Score: 0.7480
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 | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.6289 | 1.0 | 29 | 0.5587 | 0.6838 | 0.8122 | 0.7480 |
| 0.61 | 2.0 | 58 | 0.5555 | 0.6838 | 0.8122 | 0.7480 |
| 0.6103 | 3.0 | 87 | 0.5550 | 0.6838 | 0.8122 | 0.7480 |
| 0.6091 | 4.0 | 116 | 0.5555 | 0.6838 | 0.8122 | 0.7480 |
| 0.6055 | 5.0 | 145 | 0.5536 | 0.6838 | 0.8122 | 0.7480 |
| 0.5956 | 6.0 | 174 | 0.5721 | 0.6838 | 0.8122 | 0.7480 |
| 0.5936 | 7.0 | 203 | 0.5714 | 0.6838 | 0.8122 | 0.7480 |
| 0.5757 | 8.0 | 232 | 0.5738 | 0.6838 | 0.8122 | 0.7480 |
| 0.5601 | 9.0 | 261 | 0.5746 | 0.6838 | 0.8122 | 0.7480 |
| 0.5489 | 10.0 | 290 | 0.5639 | 0.6838 | 0.8122 | 0.7480 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2