<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
tiny-mlm-glue-mrpc-target-glue-qqp
This model is a fine-tuned version of muhtasham/tiny-mlm-glue-mrpc on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4096
- Accuracy: 0.7995
- F1: 0.7718
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 |
---|---|---|---|---|---|
0.5796 | 0.04 | 500 | 0.5174 | 0.7297 | 0.6813 |
0.5102 | 0.09 | 1000 | 0.4804 | 0.7541 | 0.7035 |
0.4957 | 0.13 | 1500 | 0.4916 | 0.7412 | 0.7152 |
0.4798 | 0.18 | 2000 | 0.4679 | 0.7549 | 0.7221 |
0.4728 | 0.22 | 2500 | 0.4563 | 0.7624 | 0.7270 |
0.4569 | 0.26 | 3000 | 0.4501 | 0.7673 | 0.7340 |
0.4583 | 0.31 | 3500 | 0.4480 | 0.7682 | 0.7375 |
0.4502 | 0.35 | 4000 | 0.4498 | 0.7665 | 0.7387 |
0.4514 | 0.4 | 4500 | 0.4452 | 0.7681 | 0.7410 |
0.4416 | 0.44 | 5000 | 0.4209 | 0.7884 | 0.7491 |
0.4297 | 0.48 | 5500 | 0.4288 | 0.7826 | 0.7502 |
0.4299 | 0.53 | 6000 | 0.4069 | 0.8001 | 0.7559 |
0.4248 | 0.57 | 6500 | 0.4194 | 0.7896 | 0.7547 |
0.4257 | 0.62 | 7000 | 0.4063 | 0.7998 | 0.7582 |
0.418 | 0.66 | 7500 | 0.4059 | 0.8038 | 0.7639 |
0.4306 | 0.7 | 8000 | 0.4111 | 0.7964 | 0.7615 |
0.4212 | 0.75 | 8500 | 0.3990 | 0.8065 | 0.7672 |
0.4143 | 0.79 | 9000 | 0.4227 | 0.7875 | 0.7604 |
0.4121 | 0.84 | 9500 | 0.3906 | 0.8098 | 0.7667 |
0.4138 | 0.88 | 10000 | 0.3872 | 0.8152 | 0.7725 |
0.4082 | 0.92 | 10500 | 0.3843 | 0.8148 | 0.7700 |
0.4084 | 0.97 | 11000 | 0.3863 | 0.8170 | 0.7740 |
0.4067 | 1.01 | 11500 | 0.4001 | 0.8037 | 0.7707 |
0.3854 | 1.06 | 12000 | 0.3814 | 0.8182 | 0.7756 |
0.3945 | 1.1 | 12500 | 0.3861 | 0.8132 | 0.7761 |
0.3831 | 1.14 | 13000 | 0.3917 | 0.8110 | 0.7750 |
0.3722 | 1.19 | 13500 | 0.4096 | 0.7995 | 0.7718 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2