---
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