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flan-t5-qg-tarek-test-SQUAD
This model is a fine-tuned version of google/flan-t5-base on the squad dataset. It achieves the following results on the evaluation set:
- Loss: 0.6101
- Rouge1: 51.7909
- Rouge2: 29.105
- Rougel: 47.9342
- Rougelsum: 47.9206
- Gen Len: 14.3335
- Meteor: {'meteor': 0.46880070390780776}
- Bleu: {'bleu': 0.20591622940642762, 'precisions': [0.5204716701541998, 0.2619394913622878, 0.1654269529647818, 0.10906716558470096], 'brevity_penalty': 0.9246257500068106, 'length_ratio': 0.927328752862794, 'translation_length': 111349, 'reference_length': 120075}
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Meteor | Bleu |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.6576 | 1.0 | 10950 | 0.6301 | 50.2515 | 27.5194 | 46.5001 | 46.4993 | 14.0607 | {'meteor': 0.44978235923873977} | {'bleu': 0.19104342466719015, 'precisions': [0.5159747201089206, 0.2503337307531615, 0.15519111953679066, 0.10098320626550465], 'brevity_penalty': 0.9006709188377698, 'length_ratio': 0.9052925255048928, 'translation_length': 108703, 'reference_length': 120075} |
| 0.5315 | 2.0 | 21900 | 0.6101 | 51.7909 | 29.105 | 47.9342 | 47.9206 | 14.3335 | {'meteor': 0.46880070390780776} | {'bleu': 0.20591622940642762, 'precisions': [0.5204716701541998, 0.2619394913622878, 0.1654269529647818, 0.10906716558470096], 'brevity_penalty': 0.9246257500068106, 'length_ratio': 0.927328752862794, 'translation_length': 111349, 'reference_length': 120075} |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
