mobilebert_add_GLUE_Experiment_logit_kd_mrpc_128
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: 0.5534
- 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 |
|---|---|---|---|---|---|---|
| 0.6399 | 1.0 | 29 | 0.5562 | 0.6838 | 0.8122 | 0.7480 |
| 0.6101 | 2.0 | 58 | 0.5559 | 0.6838 | 0.8122 | 0.7480 |
| 0.6111 | 3.0 | 87 | 0.5557 | 0.6838 | 0.8122 | 0.7480 |
| 0.6104 | 4.0 | 116 | 0.5572 | 0.6838 | 0.8122 | 0.7480 |
| 0.6086 | 5.0 | 145 | 0.5550 | 0.6838 | 0.8122 | 0.7480 |
| 0.6058 | 6.0 | 174 | 0.5534 | 0.6838 | 0.8122 | 0.7480 |
| 0.6036 | 7.0 | 203 | 0.5745 | 0.6838 | 0.8122 | 0.7480 |
| 0.5969 | 8.0 | 232 | 0.5595 | 0.6838 | 0.8122 | 0.7480 |
| 0.5735 | 9.0 | 261 | 0.5699 | 0.6838 | 0.8122 | 0.7480 |
| 0.5597 | 10.0 | 290 | 0.5608 | 0.6838 | 0.8122 | 0.7480 |
| 0.5456 | 11.0 | 319 | 0.5714 | 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