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t5-base_cola_mare_ar38_ex0_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: 0.5879
- Accuracy: 0.8360
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 |
|---|---|---|---|---|
| 0.451 | 0.19 | 50 | 0.8237 | 0.8198 |
| 0.3577 | 0.37 | 100 | 0.5307 | 0.8236 |
| 0.3737 | 0.56 | 150 | 0.5634 | 0.8111 |
| 0.38 | 0.75 | 200 | 0.5525 | 0.8274 |
| 0.4106 | 0.93 | 250 | 0.4820 | 0.8245 |
| 0.2847 | 1.12 | 300 | 0.6420 | 0.8188 |
| 0.271 | 1.31 | 350 | 0.5675 | 0.8341 |
| 0.3315 | 1.5 | 400 | 0.5231 | 0.8370 |
| 0.2774 | 1.68 | 450 | 0.5529 | 0.8399 |
| 0.2822 | 1.87 | 500 | 0.5359 | 0.8351 |
| 0.2225 | 2.06 | 550 | 0.5540 | 0.8322 |
| 0.3247 | 2.24 | 600 | 0.5564 | 0.8428 |
| 0.2449 | 2.43 | 650 | 0.5581 | 0.8360 |
| 0.2621 | 2.62 | 700 | 0.6079 | 0.8351 |
| 0.1814 | 2.8 | 750 | 0.5964 | 0.8380 |
| 0.3195 | 2.99 | 800 | 0.5916 | 0.8370 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1
