---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-rouge-durga-3b
  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. -->

# flan-t5-rouge-durga-3b

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2135
- Rouge1: 0.4326
- Rouge2: 0.3704
- Rougel: 0.4285
- Rougelsum: 0.4288

## 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: 0.0003
- train_batch_size: 2
- eval_batch_size: 2
- 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: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.2165        | 1.0   | 2000  | 1.9218          | 0.2604 | 0.1215 | 0.2356 | 0.2356    |
| 1.8357        | 2.0   | 4000  | 1.6767          | 0.2496 | 0.1181 | 0.2262 | 0.2264    |
| 1.11          | 3.0   | 6000  | 1.4820          | 0.2709 | 0.1363 | 0.2460 | 0.2461    |
| 1.9651        | 4.0   | 8000  | 1.3179          | 0.2750 | 0.1410 | 0.2505 | 0.2506    |
| 1.0764        | 5.0   | 10000 | 1.1559          | 0.2768 | 0.1493 | 0.2586 | 0.2586    |
| 1.0195        | 6.0   | 12000 | 1.0138          | 0.2885 | 0.1612 | 0.2685 | 0.2689    |
| 0.7455        | 7.0   | 14000 | 0.8792          | 0.2965 | 0.1739 | 0.2788 | 0.2788    |
| 0.9384        | 8.0   | 16000 | 0.7466          | 0.2998 | 0.1841 | 0.2849 | 0.2849    |
| 1.3216        | 9.0   | 18000 | 0.6505          | 0.3168 | 0.2041 | 0.3007 | 0.3010    |
| 0.9445        | 10.0  | 20000 | 0.5516          | 0.3268 | 0.2238 | 0.3133 | 0.3140    |
| 1.2079        | 11.0  | 22000 | 0.4781          | 0.3370 | 0.2381 | 0.3236 | 0.3237    |
| 0.7909        | 12.0  | 24000 | 0.4186          | 0.3394 | 0.2439 | 0.3249 | 0.3250    |
| 0.4352        | 13.0  | 26000 | 0.3459          | 0.3630 | 0.2749 | 0.3503 | 0.3507    |
| 0.4925        | 14.0  | 28000 | 0.3134          | 0.3665 | 0.2798 | 0.3548 | 0.3553    |
| 0.0707        | 15.0  | 30000 | 0.2752          | 0.3828 | 0.3025 | 0.3724 | 0.3728    |
| 0.2351        | 16.0  | 32000 | 0.2579          | 0.3815 | 0.3009 | 0.3708 | 0.3711    |
| 0.9694        | 17.0  | 34000 | 0.2439          | 0.3874 | 0.3103 | 0.3788 | 0.3795    |
| 0.6217        | 18.0  | 36000 | 0.2273          | 0.4037 | 0.3282 | 0.3956 | 0.3959    |
| 0.0914        | 19.0  | 38000 | 0.2121          | 0.4055 | 0.3343 | 0.3981 | 0.3987    |
| 0.0534        | 20.0  | 40000 | 0.2006          | 0.4134 | 0.3444 | 0.4066 | 0.4067    |
| 0.1081        | 21.0  | 42000 | 0.2009          | 0.4181 | 0.3514 | 0.4131 | 0.4132    |
| 0.0786        | 22.0  | 44000 | 0.2086          | 0.4182 | 0.3488 | 0.4112 | 0.4118    |
| 0.0364        | 23.0  | 46000 | 0.2047          | 0.4182 | 0.3508 | 0.4110 | 0.4114    |
| 0.0568        | 24.0  | 48000 | 0.2058          | 0.4227 | 0.3570 | 0.4175 | 0.4177    |
| 0.1106        | 25.0  | 50000 | 0.2073          | 0.4211 | 0.3566 | 0.4159 | 0.4164    |
| 0.0733        | 26.0  | 52000 | 0.2075          | 0.4248 | 0.3603 | 0.4195 | 0.4199    |
| 0.1169        | 27.0  | 54000 | 0.2123          | 0.4286 | 0.3650 | 0.4244 | 0.4247    |
| 0.0892        | 28.0  | 56000 | 0.2109          | 0.4327 | 0.3704 | 0.4281 | 0.4285    |
| 0.045         | 29.0  | 58000 | 0.2107          | 0.4339 | 0.3715 | 0.4300 | 0.4302    |
| 0.0908        | 30.0  | 60000 | 0.2135          | 0.4326 | 0.3704 | 0.4285 | 0.4288    |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1