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---
base_model: ybelkada/flan-t5-xl-sharded-bf16
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flanT5-xl-3.2
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. -->
# flanT5-xl-3.2
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: 0.6816
- Rouge1: 32.8295
- Rouge2: 24.633
- Rougel: 29.5824
- Rougelsum: 29.842
- Gen Len: 10.9596
## 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: 3e-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: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 362 | 4.1881 | 14.6341 | 9.0532 | 12.5623 | 12.7062 | 15.8012 |
| 19.4437 | 2.0 | 724 | 0.8038 | 31.6983 | 24.0636 | 28.4549 | 28.672 | 10.6522 |
| 0.8703 | 3.0 | 1086 | 0.7598 | 32.6624 | 24.6635 | 29.339 | 29.5778 | 10.5311 |
| 0.8703 | 4.0 | 1448 | 0.7359 | 32.6045 | 24.52 | 29.2079 | 29.466 | 10.6304 |
| 0.7965 | 5.0 | 1810 | 0.7155 | 33.1775 | 25.1312 | 29.924 | 30.1659 | 10.5901 |
| 0.7601 | 6.0 | 2172 | 0.7023 | 32.5547 | 24.3195 | 29.2416 | 29.5173 | 10.9099 |
| 0.7475 | 7.0 | 2534 | 0.6923 | 33.0802 | 24.8653 | 29.769 | 30.0683 | 10.7640 |
| 0.7475 | 8.0 | 2896 | 0.6858 | 32.6578 | 24.333 | 29.3174 | 29.6478 | 11.0435 |
| 0.7287 | 9.0 | 3258 | 0.6827 | 32.9542 | 24.7132 | 29.6381 | 29.928 | 10.9193 |
| 0.7215 | 10.0 | 3620 | 0.6816 | 32.8295 | 24.633 | 29.5824 | 29.842 | 10.9596 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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