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t5-base-pointer-adv-top_v2
This model is a fine-tuned version of google/mt5-base on the top_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0255
- Exact Match: 0.8472
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 |
---|---|---|---|---|
2.2938 | 0.41 | 200 | 0.5532 | 0.0012 |
0.671 | 0.82 | 400 | 0.1624 | 0.1610 |
0.5276 | 1.23 | 600 | 0.0692 | 0.2157 |
0.4196 | 1.64 | 800 | 0.0491 | 0.2259 |
0.3593 | 2.05 | 1000 | 0.0400 | 0.2291 |
0.3471 | 2.46 | 1200 | 0.0335 | 0.2297 |
0.3416 | 2.87 | 1400 | 0.0307 | 0.2318 |
0.3351 | 3.29 | 1600 | 0.0307 | 0.2334 |
0.3316 | 3.7 | 1800 | 0.0297 | 0.2343 |
0.3312 | 4.11 | 2000 | 0.0282 | 0.2344 |
0.3271 | 4.52 | 2200 | 0.0262 | 0.2365 |
0.3241 | 4.93 | 2400 | 0.0263 | 0.2365 |
0.3227 | 5.34 | 2600 | 0.0259 | 0.2368 |
0.3201 | 5.75 | 2800 | 0.0257 | 0.2365 |
0.3227 | 6.16 | 3000 | 0.0255 | 0.2365 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2