mobilebert_sa_GLUE_Experiment_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: 0.6220
- 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 |
---|---|---|---|---|---|---|
0.6454 | 1.0 | 29 | 0.6241 | 0.6838 | 0.8122 | 0.7480 |
0.63 | 2.0 | 58 | 0.6239 | 0.6838 | 0.8122 | 0.7480 |
0.6312 | 3.0 | 87 | 0.6246 | 0.6838 | 0.8122 | 0.7480 |
0.6305 | 4.0 | 116 | 0.6247 | 0.6838 | 0.8122 | 0.7480 |
0.6295 | 5.0 | 145 | 0.6226 | 0.6838 | 0.8122 | 0.7480 |
0.6276 | 6.0 | 174 | 0.6220 | 0.6838 | 0.8122 | 0.7480 |
0.6261 | 7.0 | 203 | 0.6228 | 0.6838 | 0.8122 | 0.7480 |
0.6007 | 8.0 | 232 | 0.6695 | 0.6373 | 0.7508 | 0.6940 |
0.5159 | 9.0 | 261 | 0.6623 | 0.6985 | 0.7831 | 0.7408 |
0.4232 | 10.0 | 290 | 0.6507 | 0.6789 | 0.7681 | 0.7235 |
0.3418 | 11.0 | 319 | 0.8759 | 0.6740 | 0.7646 | 0.7193 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
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Dataset used to train gokuls/mobilebert_sa_GLUE_Experiment_mrpc_128
Evaluation results
- Accuracy on GLUE MRPCvalidation set self-reported0.684
- F1 on GLUE MRPCvalidation set self-reported0.812