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t5-base_cola_mare_ar9_ex29_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: 0.6188
- Accuracy: 0.8341
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 |
|---|---|---|---|---|
| 0.5148 | 0.19 | 50 | 0.8585 | 0.8188 |
| 0.4482 | 0.37 | 100 | 0.6410 | 0.8255 |
| 0.4572 | 0.56 | 150 | 0.6223 | 0.8284 |
| 0.4239 | 0.75 | 200 | 0.6037 | 0.8217 |
| 0.4716 | 0.93 | 250 | 0.5145 | 0.8313 |
| 0.3453 | 1.12 | 300 | 0.6653 | 0.8207 |
| 0.3124 | 1.31 | 350 | 0.5926 | 0.8341 |
| 0.3832 | 1.5 | 400 | 0.5726 | 0.8265 |
| 0.3035 | 1.68 | 450 | 0.5937 | 0.8313 |
| 0.3068 | 1.87 | 500 | 0.5681 | 0.8274 |
| 0.2659 | 2.06 | 550 | 0.6007 | 0.8265 |
| 0.3598 | 2.24 | 600 | 0.5988 | 0.8351 |
| 0.3051 | 2.43 | 650 | 0.5925 | 0.8360 |
| 0.309 | 2.62 | 700 | 0.6517 | 0.8332 |
| 0.209 | 2.8 | 750 | 0.6257 | 0.8332 |
| 0.3505 | 2.99 | 800 | 0.6252 | 0.8341 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1
