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---
base_model: csebuetnlp/banglat5
tags:
- generated_from_trainer
model-index:
- name: banglat5-finetuned-new-method-new
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# banglat5-finetuned-new-method-new
This model is a fine-tuned version of [csebuetnlp/banglat5](https://huggingface.co/csebuetnlp/banglat5) on the None dataset.
It achieves the following results on the evaluation set:
- Rouge1 Precision: 26.1936
- Rouge1 Recall: 27.4839
- Rouge1 Fmeasure: 26.0831
- Rouge2 Precision: 10.5258
- Rouge2 Recall: 11.6544
- Rouge2 Fmeasure: 10.651
- Rougel Precision: 24.2917
- Rougel Recall: 25.5269
- Rougel Fmeasure: 24.1921
- Gen Len: 8.6402
- Loss: 2.8106
## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|:-------:|:---------------:|
| 4.1475 | 1.0 | 202 | 28.4204 | 31.0145 | 28.5051 | 12.7947 | 13.7716 | 12.4938 | 26.467 | 28.917 | 26.5293 | 11.3871 | 3.2546 |
| 3.741 | 2.0 | 404 | 25.0778 | 26.2399 | 24.7974 | 9.4574 | 10.3436 | 9.4444 | 23.2601 | 24.4534 | 23.0588 | 8.6824 | 2.9268 |
| 3.2953 | 3.0 | 606 | 25.9864 | 26.6166 | 25.5881 | 10.0107 | 10.6915 | 9.9945 | 23.7579 | 24.458 | 23.4435 | 8.4144 | 2.8387 |
| 2.9438 | 4.0 | 808 | 26.1936 | 27.4839 | 26.0831 | 10.5258 | 11.6544 | 10.651 | 24.2917 | 25.5269 | 24.1921 | 8.6402 | 2.8106 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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