byt5-base-mtop
This model is a fine-tuned version of google/byt5-base on the mtop dataset. It achieves the following results on the evaluation set:
- Loss: 0.0704
- Exact Match: 0.7978
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 |
---|---|---|---|---|
0.5459 | 6.65 | 200 | 0.0964 | 0.2107 |
0.0433 | 13.33 | 400 | 0.0704 | 0.3056 |
0.0153 | 19.98 | 600 | 0.0764 | 0.3025 |
0.0081 | 26.65 | 800 | 0.0815 | 0.3123 |
0.0045 | 33.33 | 1000 | 0.0904 | 0.3065 |
0.003 | 39.98 | 1200 | 0.0945 | 0.3060 |
0.0021 | 46.65 | 1400 | 0.0969 | 0.3087 |
0.0016 | 53.33 | 1600 | 0.1017 | 0.3105 |
0.0015 | 59.98 | 1800 | 0.1001 | 0.3096 |
0.001 | 66.65 | 2000 | 0.1059 | 0.3087 |
0.0006 | 73.33 | 2200 | 0.1041 | 0.3105 |
0.0005 | 79.98 | 2400 | 0.1083 | 0.3083 |
0.0003 | 86.65 | 2600 | 0.1115 | 0.3096 |
0.0002 | 93.33 | 2800 | 0.1130 | 0.3119 |
0.0002 | 99.98 | 3000 | 0.1131 | 0.3114 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2
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