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tiny-mlm-glue-rte-target-glue-qqp
This model is a fine-tuned version of muhtasham/tiny-mlm-glue-rte on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4155
- Accuracy: 0.7949
- F1: 0.7691
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
- num_epochs: 200
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.5776 | 0.04 | 500 | 0.5189 | 0.7264 | 0.6855 |
0.5081 | 0.09 | 1000 | 0.4824 | 0.7519 | 0.7059 |
0.4951 | 0.13 | 1500 | 0.4940 | 0.7377 | 0.7141 |
0.4792 | 0.18 | 2000 | 0.4704 | 0.7526 | 0.7221 |
0.4722 | 0.22 | 2500 | 0.4571 | 0.7618 | 0.7277 |
0.4557 | 0.26 | 3000 | 0.4496 | 0.7677 | 0.7346 |
0.4567 | 0.31 | 3500 | 0.4480 | 0.7677 | 0.7378 |
0.4497 | 0.35 | 4000 | 0.4502 | 0.7655 | 0.7386 |
0.4503 | 0.4 | 4500 | 0.4426 | 0.7712 | 0.7432 |
0.4412 | 0.44 | 5000 | 0.4216 | 0.7889 | 0.7501 |
0.4291 | 0.48 | 5500 | 0.4284 | 0.7837 | 0.7515 |
0.4293 | 0.53 | 6000 | 0.4075 | 0.8004 | 0.7577 |
0.4241 | 0.57 | 6500 | 0.4230 | 0.7879 | 0.7559 |
0.4253 | 0.62 | 7000 | 0.4067 | 0.8002 | 0.7601 |
0.4166 | 0.66 | 7500 | 0.4083 | 0.8026 | 0.7646 |
0.4302 | 0.7 | 8000 | 0.4121 | 0.7964 | 0.7624 |
0.4206 | 0.75 | 8500 | 0.3993 | 0.8051 | 0.7667 |
0.4147 | 0.79 | 9000 | 0.4202 | 0.7884 | 0.7610 |
0.4117 | 0.84 | 9500 | 0.3915 | 0.8094 | 0.7677 |
0.4131 | 0.88 | 10000 | 0.3863 | 0.8156 | 0.7735 |
0.4089 | 0.92 | 10500 | 0.3832 | 0.8157 | 0.7713 |
0.4086 | 0.97 | 11000 | 0.3836 | 0.8180 | 0.7732 |
0.406 | 1.01 | 11500 | 0.4042 | 0.8018 | 0.7707 |
0.3854 | 1.06 | 12000 | 0.3819 | 0.8182 | 0.7763 |
0.3952 | 1.1 | 12500 | 0.3836 | 0.8149 | 0.7771 |
0.3827 | 1.14 | 13000 | 0.3898 | 0.8134 | 0.7766 |
0.3719 | 1.19 | 13500 | 0.4155 | 0.7949 | 0.7691 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2