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t5-base_cola_mare_ar28_ex10_size-16_epochs-3_decoder_all_sparsity20_mare_mlp
This model is a fine-tuned version of t5-base on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.5948
- Accuracy: 0.8351
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 1
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4831 | 0.19 | 50 | 0.8408 | 0.8236 |
0.3951 | 0.37 | 100 | 0.5698 | 0.8274 |
0.3995 | 0.56 | 150 | 0.5848 | 0.8159 |
0.3874 | 0.75 | 200 | 0.5940 | 0.8236 |
0.4433 | 0.93 | 250 | 0.4991 | 0.8226 |
0.3027 | 1.12 | 300 | 0.6543 | 0.8178 |
0.2847 | 1.31 | 350 | 0.5897 | 0.8322 |
0.3451 | 1.5 | 400 | 0.5350 | 0.8332 |
0.2832 | 1.68 | 450 | 0.5703 | 0.8341 |
0.2801 | 1.87 | 500 | 0.5522 | 0.8274 |
0.2293 | 2.06 | 550 | 0.5552 | 0.8322 |
0.343 | 2.24 | 600 | 0.5687 | 0.8370 |
0.2468 | 2.43 | 650 | 0.5660 | 0.8341 |
0.2811 | 2.62 | 700 | 0.6346 | 0.8341 |
0.1944 | 2.8 | 750 | 0.6052 | 0.8360 |
0.3288 | 2.99 | 800 | 0.5984 | 0.8351 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1