---
base_model: ybelkada/flan-t5-xl-sharded-bf16
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-xl-gen6
  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-xl-gen6

This model is a fine-tuned version of [ybelkada/flan-t5-xl-sharded-bf16](https://huggingface.co./ybelkada/flan-t5-xl-sharded-bf16) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4978
- Rouge1: 29.5362
- Rouge2: 20.6621
- Rougel: 25.7689
- Rougelsum: 26.2351
- Gen Len: 12.7388

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 800
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 328  | 0.6921          | 34.9112 | 26.7503 | 31.4124 | 31.7295   | 10.0172 |
| 6.8746        | 2.0   | 656  | 0.6025          | 33.9134 | 25.3236 | 30.1968 | 30.472    | 10.8454 |
| 6.8746        | 3.0   | 984  | 0.5687          | 31.6178 | 22.9463 | 27.8758 | 28.3572   | 11.8729 |
| 0.6462        | 4.0   | 1312 | 0.5355          | 30.8157 | 22.1783 | 27.1641 | 27.569    | 12.1306 |
| 0.5618        | 5.0   | 1640 | 0.5160          | 29.9183 | 21.0842 | 26.1671 | 26.5965   | 12.5017 |
| 0.5618        | 6.0   | 1968 | 0.5025          | 29.7823 | 21.1443 | 26.0286 | 26.5215   | 12.5086 |
| 0.498         | 7.0   | 2296 | 0.4978          | 29.1043 | 20.2391 | 25.3347 | 25.804    | 12.8969 |
| 0.4551        | 8.0   | 2624 | 0.4978          | 29.5362 | 20.6621 | 25.7689 | 26.2351   | 12.7388 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0