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EN_mt5-small_5_wikiSQL
This model is a fine-tuned version of google/mt5-small on the wikisql dataset. It achieves the following results on the evaluation set:
- Loss: 0.1353
- Rouge2 Precision: 0.8272
- Rouge2 Recall: 0.7504
- Rouge2 Fmeasure: 0.7811
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.286 | 1.0 | 4049 | 0.1954 | 0.7917 | 0.7111 | 0.7421 |
| 0.2149 | 2.0 | 8098 | 0.1560 | 0.815 | 0.7378 | 0.768 |
| 0.1892 | 3.0 | 12147 | 0.1436 | 0.8229 | 0.7452 | 0.7762 |
| 0.1792 | 4.0 | 16196 | 0.1383 | 0.826 | 0.7494 | 0.7799 |
| 0.1744 | 5.0 | 20245 | 0.1353 | 0.8272 | 0.7504 | 0.7811 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.7.dev0
- Tokenizers 0.13.3
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("e22vvb/EN_mt5-small_5_wikiSQL") model = AutoModelForSeq2SeqLM.from_pretrained("e22vvb/EN_mt5-small_5_wikiSQL")