<!-- 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-mnli
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: 0.7870
- Accuracy: 0.6519
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 |
---|---|---|---|---|
1.076 | 0.04 | 500 | 1.0342 | 0.4657 |
1.0114 | 0.08 | 1000 | 0.9714 | 0.5393 |
0.9654 | 0.12 | 1500 | 0.9268 | 0.5736 |
0.9381 | 0.16 | 2000 | 0.9120 | 0.5849 |
0.9266 | 0.2 | 2500 | 0.8942 | 0.5953 |
0.9171 | 0.24 | 3000 | 0.8783 | 0.6014 |
0.9009 | 0.29 | 3500 | 0.8687 | 0.6085 |
0.8932 | 0.33 | 4000 | 0.8567 | 0.6191 |
0.8767 | 0.37 | 4500 | 0.8524 | 0.6171 |
0.8768 | 0.41 | 5000 | 0.8436 | 0.6231 |
0.8702 | 0.45 | 5500 | 0.8374 | 0.6220 |
0.8673 | 0.49 | 6000 | 0.8345 | 0.6271 |
0.8684 | 0.53 | 6500 | 0.8274 | 0.6274 |
0.8606 | 0.57 | 7000 | 0.8282 | 0.6298 |
0.8528 | 0.61 | 7500 | 0.8146 | 0.6363 |
0.8529 | 0.65 | 8000 | 0.8103 | 0.6406 |
0.8467 | 0.69 | 8500 | 0.8237 | 0.6320 |
0.8478 | 0.73 | 9000 | 0.7964 | 0.6473 |
0.8399 | 0.77 | 9500 | 0.8081 | 0.6391 |
0.8295 | 0.81 | 10000 | 0.7954 | 0.6475 |
0.833 | 0.86 | 10500 | 0.7994 | 0.6439 |
0.8316 | 0.9 | 11000 | 0.7886 | 0.6513 |
0.8239 | 0.94 | 11500 | 0.7847 | 0.6544 |
0.8247 | 0.98 | 12000 | 0.7848 | 0.6512 |
0.81 | 1.02 | 12500 | 0.7915 | 0.6507 |
0.8059 | 1.06 | 13000 | 0.7870 | 0.6519 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2