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---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
datasets:
- lilferrit/xsum_t5_distillation
metrics:
- rouge
model-index:
- name: xsum_aligned_smallT5_full
results:
- task:
name: Summarization
type: summarization
dataset:
name: lilferrit/xsum_t5_distillation
type: lilferrit/xsum_t5_distillation
metrics:
- name: Rouge1
type: rouge
value: 22.8498
---
<!-- 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. -->
# xsum_aligned_smallT5_full
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the lilferrit/xsum_t5_distillation dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4093
- Rouge1: 22.8498
- Rouge2: 4.7818
- Rougel: 17.2861
- Rougelsum: 18.0665
- Gen Len: 33.6366
## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adafactor
- lr_scheduler_type: constant
- training_steps: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| No log | 0.0 | 5 | 2.6444 | 22.3341 | 4.3395 | 16.2507 | 17.8303 | 46.2437 |
| No log | 0.0 | 10 | 2.4093 | 22.8498 | 4.7818 | 17.2861 | 18.0665 | 33.6366 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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