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---
base_model: ybelkada/flan-t5-xl-sharded-bf16
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-xl-gen5
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-gen5
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: 0.6594
- Rouge1: 34.2696
- Rouge2: 25.7973
- Rougel: 30.5609
- Rougelsum: 30.9651
- Gen Len: 10.5326
## 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: 2e-05
- 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: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 328 | 8.0966 | 16.5418 | 10.3523 | 13.972 | 14.1918 | 15.5773 |
| 18.3143 | 2.0 | 656 | 0.9260 | 31.5806 | 27.0287 | 29.6916 | 30.0327 | 8.8969 |
| 18.3143 | 3.0 | 984 | 0.7708 | 22.6847 | 15.805 | 19.6336 | 19.8945 | 13.8076 |
| 1.0739 | 4.0 | 1312 | 0.7308 | 35.1675 | 27.3998 | 31.8527 | 32.0356 | 9.6186 |
| 0.8085 | 5.0 | 1640 | 0.7084 | 34.4346 | 26.202 | 30.8999 | 31.212 | 10.1168 |
| 0.8085 | 6.0 | 1968 | 0.6924 | 34.3345 | 26.0144 | 30.692 | 31.0384 | 10.2680 |
| 0.7597 | 7.0 | 2296 | 0.6813 | 34.3854 | 26.0495 | 30.8335 | 31.1696 | 10.3196 |
| 0.7442 | 8.0 | 2624 | 0.6729 | 34.3758 | 26.0079 | 30.7863 | 31.1239 | 10.3608 |
| 0.7442 | 9.0 | 2952 | 0.6670 | 34.2115 | 25.7443 | 30.5369 | 30.9282 | 10.4983 |
| 0.7252 | 10.0 | 3280 | 0.6625 | 34.2518 | 25.7147 | 30.5433 | 30.9116 | 10.5292 |
| 0.7168 | 11.0 | 3608 | 0.6601 | 34.0539 | 25.5073 | 30.329 | 30.6828 | 10.6186 |
| 0.7168 | 12.0 | 3936 | 0.6594 | 34.2696 | 25.7973 | 30.5609 | 30.9651 | 10.5326 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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