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small-vanilla-target-glue-mrpc-linear-probe
This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5860
- Accuracy: 0.7010
- F1: 0.8174
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6358 | 4.35 | 500 | 0.6136 | 0.6838 | 0.8111 |
| 0.6123 | 8.7 | 1000 | 0.6068 | 0.6863 | 0.8129 |
| 0.6054 | 13.04 | 1500 | 0.5990 | 0.6838 | 0.8095 |
| 0.6008 | 17.39 | 2000 | 0.5962 | 0.6912 | 0.8136 |
| 0.595 | 21.74 | 2500 | 0.5925 | 0.7059 | 0.8209 |
| 0.5916 | 26.09 | 3000 | 0.5898 | 0.7034 | 0.8191 |
| 0.5885 | 30.43 | 3500 | 0.5906 | 0.7010 | 0.8185 |
| 0.5915 | 34.78 | 4000 | 0.5860 | 0.7010 | 0.8174 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
