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---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned
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: 0.4303256962227823
---
<!-- 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
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: 1.7974
- Rouge1: 0.4303
- Rouge2: 0.2038
- Rougel: 0.3736
- Rougelsum: 0.3734
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.1585 | 1.0 | 1842 | 1.9205 | 0.4074 | 0.1838 | 0.3517 | 0.3518 |
| 2.1545 | 2.0 | 3684 | 1.8882 | 0.4120 | 0.1914 | 0.3592 | 0.3588 |
| 2.0888 | 3.0 | 5526 | 1.8290 | 0.4196 | 0.1939 | 0.3603 | 0.3601 |
| 2.0272 | 4.0 | 7368 | 1.8269 | 0.4215 | 0.1975 | 0.3637 | 0.3635 |
| 1.9871 | 5.0 | 9210 | 1.8224 | 0.4231 | 0.1943 | 0.3634 | 0.3633 |
| 1.9535 | 6.0 | 11052 | 1.8055 | 0.4285 | 0.2030 | 0.3715 | 0.3715 |
| 1.9322 | 7.0 | 12894 | 1.7954 | 0.4270 | 0.2018 | 0.3698 | 0.3697 |
| 1.9181 | 8.0 | 14736 | 1.7974 | 0.4303 | 0.2038 | 0.3736 | 0.3734 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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