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---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned_samsum_summarization_model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: validation
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 39.9323
---
<!-- 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. -->
# mt5-small-finetuned_samsum_summarization_model
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9328
- Rouge1: 39.9323
- Rouge2: 18.0293
- Rougel: 34.3611
- Rougelsum: 37.3087
## 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: 5.6e-05
- train_batch_size: 14
- eval_batch_size: 14
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 4.5012 | 1.0 | 1050 | 2.1992 | 34.6608 | 14.0886 | 29.8674 | 32.1737 |
| 2.6852 | 2.0 | 2100 | 2.1014 | 38.1793 | 16.0747 | 32.5426 | 35.4332 |
| 2.4933 | 3.0 | 3150 | 2.0319 | 38.4414 | 16.4993 | 32.6973 | 35.8539 |
| 2.3933 | 4.0 | 4200 | 1.9910 | 39.2966 | 17.1718 | 33.5556 | 36.802 |
| 2.3273 | 5.0 | 5250 | 1.9764 | 39.7619 | 17.7287 | 33.9838 | 37.1345 |
| 2.2783 | 6.0 | 6300 | 1.9503 | 39.9351 | 17.8312 | 34.2641 | 37.2625 |
| 2.2543 | 7.0 | 7350 | 1.9350 | 39.9551 | 17.918 | 34.3361 | 37.2039 |
| 2.2383 | 8.0 | 8400 | 1.9328 | 39.9323 | 18.0293 | 34.3611 | 37.3087 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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