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t5-base-vanilla-cstop_artificial
This model is a fine-tuned version of google/mt5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1598
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.2724 | 28.5 | 200 | 0.0776 |
| 0.0151 | 57.13 | 400 | 0.1004 |
| 0.1727 | 85.63 | 600 | 0.1202 |
| 0.0133 | 114.25 | 800 | 0.1005 |
| 0.0044 | 142.75 | 1000 | 0.1131 |
| 0.0022 | 171.38 | 1200 | 0.1285 |
| 0.0018 | 199.88 | 1400 | 0.1349 |
| 0.0014 | 228.5 | 1600 | 0.1451 |
| 0.003 | 257.13 | 1800 | 0.1215 |
| 0.003 | 285.63 | 2000 | 0.1345 |
| 0.0012 | 314.25 | 2200 | 0.1520 |
| 0.001 | 342.75 | 2400 | 0.1486 |
| 0.0008 | 371.38 | 2600 | 0.1559 |
| 0.0007 | 399.88 | 2800 | 0.1590 |
| 0.0006 | 428.5 | 3000 | 0.1598 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2
