---
library_name: transformers
license: apache-2.0
base_model: t5-base
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: insightSumm_t5_finetuned_model_final-insightSumm__2025-05-06_02.19.20
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mishikaj162001-cisco/insightSumm_t5_finetuned_model_final/runs/w3wc2hi5)
# insightSumm_t5_finetuned_model_final-insightSumm__2025-05-06_02.19.20

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3468
- Rouge1: 89.1089
- Rouge2: 86.5989
- Rougel: 88.8703
- Rougelsum: 88.8963

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.2422        | 1.0   | 3168  | 0.3808          | 88.8866 | 86.4314 | 88.6547 | 88.6723   |
| 0.2168        | 2.0   | 6336  | 0.3629          | 88.9098 | 86.4533 | 88.6846 | 88.7028   |
| 0.6073        | 3.0   | 9504  | 0.3476          | 89.0326 | 86.5194 | 88.786  | 88.8062   |
| 0.3439        | 4.0   | 12672 | 0.3468          | 89.1089 | 86.5989 | 88.8703 | 88.8963   |
| 0.4147        | 5.0   | 15840 | 0.3453          | 89.0482 | 86.5523 | 88.8104 | 88.8276   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.7.0+cu126
- Datasets 3.5.1
- Tokenizers 0.21.1