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t5-base-pointer-adv-cstop_artificial
This model is a fine-tuned version of google/mt5-base on the cstop_artificial dataset. It achieves the following results on the evaluation set:
- Loss: 0.0728
- Exact Match: 0.7925
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 | Exact Match |
|---|---|---|---|---|
| 1.7423 | 12.5 | 200 | 0.1173 | 0.2397 |
| 0.3678 | 25.0 | 400 | 0.0728 | 0.3363 |
| 0.3202 | 37.5 | 600 | 0.0879 | 0.3381 |
| 0.3452 | 50.0 | 800 | 0.0908 | 0.3363 |
| 0.3099 | 62.5 | 1000 | 0.1056 | 0.3435 |
| 0.3057 | 75.0 | 1200 | 0.1109 | 0.3470 |
| 0.3045 | 87.5 | 1400 | 0.1273 | 0.3453 |
| 0.3052 | 100.0 | 1600 | 0.1065 | 0.3417 |
| 0.3037 | 112.5 | 1800 | 0.1387 | 0.3381 |
| 0.3036 | 125.0 | 2000 | 0.1421 | 0.3453 |
| 0.3023 | 137.5 | 2200 | 0.1649 | 0.3399 |
| 0.3028 | 150.0 | 2400 | 0.1574 | 0.3399 |
| 0.3025 | 162.5 | 2600 | 0.1563 | 0.3399 |
| 0.3017 | 175.0 | 2800 | 0.1589 | 0.3399 |
| 0.302 | 187.5 | 3000 | 0.1587 | 0.3417 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2
