squad-bn-mt5-base2
This model is a fine-tuned version of google/mt5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5309
- Rouge1 Precision: 37.5039
- Rouge1 Recall: 30.4476
- Rouge1 Fmeasure: 32.6695
- Rouge2 Precision: 16.2843
- Rouge2 Recall: 12.9093
- Rouge2 Fmeasure: 13.9246
- Rougel Precision: 35.2648
- Rougel Recall: 28.6919
- Rougel Fmeasure: 30.7578
- Rougelsum Precision: 35.2646
- Rougelsum Recall: 28.6829
- Rougelsum Fmeasure: 30.7527
- Bleu-1: 23.9098
- Bleu-2: 14.7458
- Bleu-3: 9.684
- Bleu-4: 6.6217
- Meteor: 0.142
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: 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: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 Precision | Rouge1 Recall | Rouge1 Fmeasure | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Rougel Precision | Rougel Recall | Rougel Fmeasure | Rougelsum Precision | Rougelsum Recall | Rougelsum Fmeasure | Bleu-1 | Bleu-2 | Bleu-3 | Bleu-4 | Meteor |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.698 | 1.0 | 6769 | 0.5654 | 35.1173 | 28.5689 | 30.6164 | 14.7565 | 11.6885 | 12.6012 | 33.0241 | 26.9309 | 28.8245 | 33.0061 | 26.9075 | 28.807 | 22.6163 | 13.6841 | 8.8346 | 5.926 | 0.1314 |
0.6202 | 2.0 | 13538 | 0.5437 | 36.3795 | 29.5116 | 31.6675 | 15.5398 | 12.3022 | 13.2805 | 34.3036 | 27.8749 | 29.8881 | 34.2498 | 27.8384 | 29.8439 | 23.2744 | 14.1999 | 9.2715 | 6.2908 | 0.1364 |
0.5878 | 3.0 | 20307 | 0.5322 | 37.2522 | 30.1185 | 32.3701 | 16.0437 | 12.6396 | 13.6664 | 35.0062 | 28.3657 | 30.4487 | 34.9742 | 28.3319 | 30.4195 | 23.7569 | 14.5781 | 9.5429 | 6.52 | 0.1407 |
0.5761 | 4.0 | 27076 | 0.5309 | 37.5 | 30.4513 | 32.6723 | 16.2813 | 12.9079 | 13.9284 | 35.2662 | 28.6924 | 30.755 | 35.2509 | 28.6759 | 30.7444 | 23.9098 | 14.7458 | 9.684 | 6.6217 | 0.142 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
Citation
@misc {tahsin_mayeesha_2023, author = { {Tahsin Mayeesha} }, title = { squad-bn-mt5-base2 (Revision 4ab9b63) }, year = 2023, url = { https://huggingface.co/Tahsin-Mayeesha/squad-bn-mt5-base2 }, doi = { 10.57967/hf/0940 }, publisher = { Hugging Face } }
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