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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- summarize_from_feedback
metrics:
- rouge
model-index:
- name: flan-t5-small-finetuned-openai-summarize_from_feedback
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: summarize_from_feedback
type: summarize_from_feedback
config: comparisons
split: train
args: comparisons
metrics:
- name: Rouge1
type: rouge
value: 27.2966
---
<!-- 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 (small) fine-tuned on OpenAI summarize_from_feedback for summarizing
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the summarize_from_feedback dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1488
- Rouge1: 27.2966
- Rouge2: 9.5886
- Rougel: 22.1999
- Rougelsum: 23.6317
- Gen Len: 18.9310
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.2472 | 1.0 | 2902 | 2.1882 | 26.2033 | 8.83 | 21.3673 | 22.7758 | 18.9234 |
| 2.1142 | 2.0 | 5804 | 2.1608 | 27.1972 | 9.4269 | 22.1761 | 23.6252 | 18.8796 |
| 2.0484 | 3.0 | 8706 | 2.1524 | 27.0963 | 9.4578 | 21.9866 | 23.5124 | 18.9033 |
| 2.0055 | 4.0 | 11608 | 2.1519 | 27.2428 | 9.5514 | 22.1542 | 23.6036 | 18.9347 |
| 1.9647 | 5.0 | 14510 | 2.1488 | 27.2966 | 9.5886 | 22.1999 | 23.6317 | 18.9310 |
| 1.9547 | 6.0 | 17412 | 2.1488 | 27.5602 | 9.673 | 22.3768 | 23.8399 | 18.9236 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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