transformers 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-cnn-dailymail-en_nlp-course-chapter7-section4
  results: []
---

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# mt5-small-finetuned-cnn-dailymail-en_nlp-course-chapter7-section4

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: 1.6856
- Rouge1: 33.1062
- Rouge2: 17.2193
- Rougel: 29.2904
- Rougelsum: 31.0641

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.5643        | 1.0   | 35890  | 1.8832          | 32.0495 | 16.2168 | 28.2966 | 30.0297   |
| 2.2043        | 2.0   | 71780  | 1.7913          | 32.3942 | 16.6084 | 28.6015 | 30.3686   |
| 2.1059        | 3.0   | 107670 | 1.7545          | 32.5226 | 16.7984 | 28.8285 | 30.5446   |
| 2.0453        | 4.0   | 143560 | 1.7311          | 32.4746 | 16.7548 | 28.7544 | 30.4887   |
| 2.0033        | 5.0   | 179450 | 1.7099          | 33.1011 | 17.2836 | 29.3355 | 31.0773   |
| 1.9721        | 6.0   | 215340 | 1.6970          | 33.0955 | 17.1866 | 29.2639 | 31.0288   |
| 1.9501        | 7.0   | 251230 | 1.6915          | 33.2428 | 17.3318 | 29.4191 | 31.1813   |
| 1.9355        | 8.0   | 287120 | 1.6856          | 33.1062 | 17.2193 | 29.2904 | 31.0641   |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.11.0+cu102
- Datasets 2.15.0
- Tokenizers 0.15.0
