<!-- 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-sst2-target-glue-qqp
This model is a fine-tuned version of muhtasham/tiny-mlm-glue-sst2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4117
- Accuracy: 0.7972
- F1: 0.7705
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 |
---|---|---|---|---|---|
0.578 | 0.04 | 500 | 0.5173 | 0.7295 | 0.6786 |
0.5102 | 0.09 | 1000 | 0.4813 | 0.7532 | 0.7023 |
0.4981 | 0.13 | 1500 | 0.4910 | 0.7409 | 0.7150 |
0.4808 | 0.18 | 2000 | 0.4655 | 0.7558 | 0.7214 |
0.4728 | 0.22 | 2500 | 0.4552 | 0.7634 | 0.7282 |
0.4557 | 0.26 | 3000 | 0.4475 | 0.7693 | 0.7353 |
0.4577 | 0.31 | 3500 | 0.4464 | 0.7690 | 0.7379 |
0.4507 | 0.35 | 4000 | 0.4495 | 0.7670 | 0.7397 |
0.4511 | 0.4 | 4500 | 0.4409 | 0.7721 | 0.7437 |
0.4414 | 0.44 | 5000 | 0.4189 | 0.7903 | 0.7499 |
0.4291 | 0.48 | 5500 | 0.4267 | 0.7838 | 0.7510 |
0.431 | 0.53 | 6000 | 0.4064 | 0.8005 | 0.7566 |
0.4236 | 0.57 | 6500 | 0.4161 | 0.7930 | 0.7573 |
0.4258 | 0.62 | 7000 | 0.4038 | 0.8030 | 0.7608 |
0.4167 | 0.66 | 7500 | 0.4066 | 0.8041 | 0.7648 |
0.4312 | 0.7 | 8000 | 0.4111 | 0.7966 | 0.7621 |
0.4203 | 0.75 | 8500 | 0.3971 | 0.8068 | 0.7671 |
0.4143 | 0.79 | 9000 | 0.4187 | 0.7894 | 0.7613 |
0.4115 | 0.84 | 9500 | 0.3884 | 0.8127 | 0.7688 |
0.4133 | 0.88 | 10000 | 0.3849 | 0.8172 | 0.7731 |
0.4091 | 0.92 | 10500 | 0.3826 | 0.8178 | 0.7725 |
0.4085 | 0.97 | 11000 | 0.3832 | 0.8186 | 0.7723 |
0.4066 | 1.01 | 11500 | 0.4000 | 0.8039 | 0.7711 |
0.3859 | 1.06 | 12000 | 0.3798 | 0.8195 | 0.7758 |
0.3955 | 1.1 | 12500 | 0.3835 | 0.8159 | 0.7781 |
0.3833 | 1.14 | 13000 | 0.3872 | 0.8138 | 0.7764 |
0.3722 | 1.19 | 13500 | 0.4117 | 0.7972 | 0.7705 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2