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---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
datasets:
- adithya7/background-summaries
metrics:
- rouge
model-index:
- name: '2023_12_18_08_41_35'
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: background_summ
type: background_summ
config: background-summ
split: validation
args: background-summ
metrics:
- name: Rouge1
type: rouge
value: 39.8
---
<!-- 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. -->
# 2023_12_18_08_41_35
This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the background_summ dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3928
- Rouge1: 39.8
- Rouge2: 18.8
- Rougel: 26.7
- Rougelsum: 36.1
- Bertscore Precision: 88.4
- Bertscore Recall: 86.8
- Bertscore F1: 87.5
## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------------------:|:----------------:|:------------:|
| 1.6858 | 1.0 | 714 | 2.0262 | 41.1 | 19.3 | 27.1 | 37.3 | 87.9 | 87.1 | 87.5 |
| 1.1309 | 2.0 | 1428 | 2.0889 | 40.8 | 19.6 | 27.3 | 37.1 | 87.8 | 87.1 | 87.4 |
| 0.7568 | 3.0 | 2142 | 2.1569 | 40.8 | 19.1 | 27.3 | 37.0 | 87.8 | 87.0 | 87.4 |
| 0.6779 | 4.0 | 2856 | 2.1800 | 39.5 | 18.4 | 26.4 | 35.9 | 87.8 | 86.7 | 87.2 |
| 0.5567 | 5.0 | 3570 | 2.2454 | 40.1 | 19.0 | 26.8 | 36.6 | 88.2 | 86.8 | 87.4 |
| 0.5264 | 6.0 | 4284 | 2.3172 | 38.8 | 18.1 | 26.1 | 35.2 | 88.0 | 86.6 | 87.3 |
| 0.5046 | 7.0 | 4998 | 2.3409 | 40.1 | 19.0 | 27.0 | 36.4 | 88.4 | 86.8 | 87.6 |
| 0.4465 | 8.0 | 5712 | 2.3751 | 39.8 | 18.7 | 26.7 | 36.1 | 88.4 | 86.7 | 87.6 |
| 0.4524 | 9.0 | 6426 | 2.3824 | 40.0 | 19.0 | 27.1 | 36.4 | 88.5 | 86.8 | 87.6 |
| 0.4308 | 10.0 | 7140 | 2.3928 | 39.8 | 18.8 | 26.7 | 36.1 | 88.4 | 86.8 | 87.5 |
### Framework versions
- Transformers 4.33.1
- Pytorch 1.13.1
- Datasets 2.14.5
- Tokenizers 0.13.3
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