transformers tensorboard safetensors mt5 text2text-generation summarization generated_from_trainer base_model:google/mt5-small base_model:finetune:google/mt5-small license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: google/mt5-small
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-mt5-small
  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. -->

# mt5-small-finetuned-mt5-small

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4415
- Rouge1: 0.1099
- Rouge2: 0.0252
- Rougel: 0.1091
- Rougelsum: 0.1092

## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.9231        | 1.0   | 12500  | 2.6899          | 0.0981 | 0.0217 | 0.0975 | 0.0976    |
| 2.9124        | 2.0   | 25000  | 2.5725          | 0.0981 | 0.0214 | 0.0974 | 0.0974    |
| 2.7986        | 3.0   | 37500  | 2.5226          | 0.1053 | 0.0243 | 0.1047 | 0.1047    |
| 2.7205        | 4.0   | 50000  | 2.4882          | 0.1069 | 0.0245 | 0.1061 | 0.1062    |
| 2.6668        | 5.0   | 62500  | 2.4613          | 0.1112 | 0.0244 | 0.1104 | 0.1105    |
| 2.624         | 6.0   | 75000  | 2.4584          | 0.111  | 0.0254 | 0.1103 | 0.1103    |
| 2.5963        | 7.0   | 87500  | 2.4448          | 0.1093 | 0.0249 | 0.1085 | 0.1087    |
| 2.5776        | 8.0   | 100000 | 2.4415          | 0.1099 | 0.0252 | 0.1091 | 0.1092    |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
