mobilebert_sa_GLUE_Experiment_data_aug_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: 0.8941
- Accuracy: 0.6032
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 |
|---|---|---|---|---|
| 0.8576 | 1.0 | 62880 | 0.8695 | 0.6149 |
| 0.7038 | 2.0 | 125760 | 0.9329 | 0.6064 |
| 0.5903 | 3.0 | 188640 | 1.0482 | 0.6056 |
| 0.4948 | 4.0 | 251520 | 1.1219 | 0.6020 |
| 0.4117 | 5.0 | 314400 | 1.2323 | 0.5938 |
| 0.3364 | 6.0 | 377280 | 1.2683 | 0.5877 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
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Dataset used to train gokuls/mobilebert_sa_GLUE_Experiment_data_aug_mnli_256
Evaluation results
- Accuracy on GLUE MNLIself-reported0.603