---
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