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---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: en_bn_summarize_v4
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_v4
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9901
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Gen Len: 18.5342
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 26.6079 | 1.0 | 615 | 19.6911 | 0.0 | 0.0 | 0.0 | 0.0 | 5.8944 |
| 22.7508 | 2.0 | 1230 | 12.3575 | 0.0 | 0.0 | 0.0 | 0.0 | 6.8447 |
| 15.4958 | 3.0 | 1845 | 4.1616 | 0.0 | 0.0 | 0.0 | 0.0 | 16.4099 |
| 7.2592 | 4.0 | 2460 | 3.5828 | 0.0 | 0.0 | 0.0 | 0.0 | 10.7702 |
| 4.7619 | 5.0 | 3075 | 3.3817 | 0.0 | 0.0 | 0.0 | 0.0 | 16.1615 |
| 4.5058 | 6.0 | 3690 | 3.2461 | 0.0 | 0.0 | 0.0 | 0.0 | 17.2733 |
| 4.3329 | 7.0 | 4305 | 3.1254 | 0.0 | 0.0 | 0.0 | 0.0 | 18.0124 |
| 4.1691 | 8.0 | 4920 | 3.0500 | 0.0 | 0.0 | 0.0 | 0.0 | 17.9689 |
| 3.9262 | 9.0 | 5535 | 2.9968 | 0.0 | 0.0 | 0.0 | 0.0 | 18.4161 |
| 3.862 | 10.0 | 6150 | 2.9901 | 0.0 | 0.0 | 0.0 | 0.0 | 18.5342 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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