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
library_name: transformers
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-synthetic-data-plus-translated-bs64-ep20
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mt5-small-synthetic-data-plus-translated-bs64-ep20

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: 1.4566
- Rouge1: 0.2300
- Rouge2: 0.1163
- Rougel: 0.2056
- Rougelsum: 0.2055

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 20.7702       | 1.0   | 19   | 11.1481         | 0.0054 | 0.0019 | 0.0053 | 0.0057    |
| 14.5169       | 2.0   | 38   | 6.9805          | 0.0043 | 0.0008 | 0.0043 | 0.0043    |
| 10.9637       | 3.0   | 57   | 5.0126          | 0.0043 | 0.0    | 0.0042 | 0.0038    |
| 8.5736        | 4.0   | 76   | 3.4889          | 0.0183 | 0.0036 | 0.0164 | 0.0164    |
| 6.9785        | 5.0   | 95   | 3.1837          | 0.0532 | 0.0068 | 0.0492 | 0.0499    |
| 5.7159        | 6.0   | 114  | 2.7398          | 0.0134 | 0.0009 | 0.0124 | 0.0127    |
| 4.7695        | 7.0   | 133  | 2.3907          | 0.0672 | 0.0248 | 0.0563 | 0.0562    |
| 4.1002        | 8.0   | 152  | 2.1993          | 0.1233 | 0.0514 | 0.1036 | 0.1038    |
| 3.6707        | 9.0   | 171  | 2.0524          | 0.1737 | 0.0689 | 0.1399 | 0.1411    |
| 3.3974        | 10.0  | 190  | 1.9375          | 0.2102 | 0.0854 | 0.1730 | 0.1733    |
| 3.1294        | 11.0  | 209  | 1.8367          | 0.2270 | 0.0974 | 0.1917 | 0.1919    |
| 3.0166        | 12.0  | 228  | 1.7489          | 0.2263 | 0.1061 | 0.1947 | 0.1956    |
| 2.7434        | 13.0  | 247  | 1.6770          | 0.2334 | 0.1073 | 0.1991 | 0.1999    |
| 2.7288        | 14.0  | 266  | 1.6183          | 0.2258 | 0.1057 | 0.1958 | 0.1967    |
| 2.6084        | 15.0  | 285  | 1.5695          | 0.2264 | 0.1089 | 0.1982 | 0.1986    |
| 2.5373        | 16.0  | 304  | 1.5259          | 0.2217 | 0.1086 | 0.1960 | 0.1961    |
| 2.4698        | 17.0  | 323  | 1.4961          | 0.2281 | 0.1124 | 0.2017 | 0.2014    |
| 2.3932        | 18.0  | 342  | 1.4754          | 0.2316 | 0.1141 | 0.2051 | 0.2048    |
| 2.375         | 19.0  | 361  | 1.4614          | 0.2281 | 0.1140 | 0.2032 | 0.2030    |
| 2.3621        | 20.0  | 380  | 1.4566          | 0.2300 | 0.1163 | 0.2056 | 0.2055    |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
