banglat5-finetuned-new-method
This model is a fine-tuned version of csebuetnlp/banglat5 on the None dataset. It achieves the following results on the evaluation set:
- Rouge1 Precision: 13.6496
- Rouge1 Recall: 27.8778
- Rouge1 Fmeasure: 17.8803
- Rouge2 Precision: 4.9428
- Rouge2 Recall: 10.9976
- Rouge2 Fmeasure: 6.6131
- Rougel Precision: 12.916
- Rougel Recall: 26.5923
- Rougel Fmeasure: 16.9585
- Gen Len: 18.6998
- Loss: 4.9511
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: 1e-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: 5
Training results
Training Loss | Epoch | Step | Rouge1 Precision | Rouge1 Recall | Rouge1 Fmeasure | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Rougel Precision | Rougel Recall | Rougel Fmeasure | Gen Len | Validation Loss |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9.5004 | 1.0 | 202 | 9.8059 | 20.2097 | 12.8916 | 2.9133 | 6.3753 | 3.8695 | 9.092 | 18.8644 | 11.9714 | 19.0 | 6.5711 |
7.6455 | 2.0 | 404 | 11.168 | 22.9627 | 14.6726 | 3.8094 | 8.4291 | 5.0876 | 10.3227 | 21.5565 | 13.6235 | 19.0 | 5.7313 |
6.8425 | 3.0 | 606 | 12.4439 | 25.6372 | 16.361 | 4.3303 | 9.7531 | 5.8212 | 11.7523 | 24.4085 | 15.4884 | 18.9851 | 5.2068 |
6.6708 | 4.0 | 808 | 13.2142 | 27.0973 | 17.3176 | 4.8216 | 10.7206 | 6.442 | 12.4235 | 25.6883 | 16.3239 | 18.7965 | 5.0076 |
6.6577 | 5.0 | 1010 | 13.6496 | 27.8778 | 17.8803 | 4.9428 | 10.9976 | 6.6131 | 12.916 | 26.5923 | 16.9585 | 18.6998 | 4.9511 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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