---
base_model: csebuetnlp/mT5_m2m_crossSum
tags:
- generated_from_trainer
model-index:
- name: en_bn_summarize_v7
  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. -->

# en_bn_summarize_v7

This model is a fine-tuned version of [csebuetnlp/mT5_m2m_crossSum](https://huggingface.co/csebuetnlp/mT5_m2m_crossSum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8058
- Rouge-1: 18.1261
- Rouge-2: 6.4386
- Rouge-l: 15.755
- Gen Len: 43.3354

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|
| 1.8582        | 1.0   | 154  | 1.8089          | 17.2361 | 6.3031  | 15.1651 | 42.4348 |
| 1.6492        | 2.0   | 308  | 1.7993          | 16.9045 | 6.083   | 14.6343 | 41.472  |
| 1.6278        | 3.0   | 462  | 1.8006          | 16.909  | 6.1661  | 14.6043 | 43.4969 |
| 1.5656        | 4.0   | 616  | 1.8016          | 17.1664 | 6.3668  | 15.0702 | 42.1925 |
| 1.5456        | 5.0   | 770  | 1.7983          | 16.8696 | 5.9485  | 14.729  | 42.2298 |
| 1.5146        | 6.0   | 924  | 1.8060          | 17.2806 | 5.98    | 14.7861 | 43.3602 |
| 1.4575        | 7.0   | 1078 | 1.8024          | 17.6126 | 6.1446  | 15.1649 | 43.3665 |
| 1.4988        | 8.0   | 1232 | 1.8046          | 17.619  | 6.1422  | 15.1738 | 43.3913 |
| 1.4637        | 9.0   | 1386 | 1.8059          | 17.6713 | 6.2475  | 15.3152 | 44.0621 |
| 1.4593        | 10.0  | 1540 | 1.8058          | 18.1261 | 6.4386  | 15.755  | 43.3354 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3