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# mt5-small-finetuned-test_76362_prefix_summarize

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: 2.9121
- Rouge1: 10.3868
- Rouge2: 2.5204
- Rougel: 8.4329
- Rougelsum: 9.8992
- Gen Len: 18.94

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:---------:|:-------:|
| 10.1311       | 0.62  | 500  | 3.2370          | 8.9071  | 1.6453 | 7.2678 | 8.52      | 18.98   |
| 4.8398        | 1.25  | 1000 | 3.1443          | 9.0606  | 1.9846 | 7.4709 | 8.5989    | 18.29   |
| 4.3499        | 1.88  | 1500 | 3.0952          | 8.3956  | 1.9098 | 6.9475 | 7.9273    | 16.84   |
| 4.2219        | 2.5   | 2000 | 3.0564          | 8.9092  | 2.0878 | 7.4312 | 8.4997    | 17.29   |
| 3.9946        | 3.12  | 2500 | 3.0379          | 8.4767  | 1.9492 | 7.067  | 8.0053    | 17.6    |
| 3.9064        | 3.75  | 3000 | 3.0056          | 8.9422  | 2.0965 | 7.3399 | 8.4327    | 17.82   |
| 3.929         | 4.38  | 3500 | 2.9832          | 9.9261  | 2.5586 | 8.0593 | 9.3784    | 18.25   |
| 3.7816        | 5.0   | 4000 | 2.9614          | 9.7556  | 2.3665 | 7.9805 | 9.3561    | 18.22   |
| 3.7658        | 5.62  | 4500 | 2.9545          | 10.6714 | 2.7593 | 8.6104 | 10.2465   | 18.73   |
| 3.7437        | 6.25  | 5000 | 2.9382          | 10.5653 | 2.8903 | 8.6845 | 10.1532   | 18.84   |
| 3.6762        | 6.88  | 5500 | 2.9316          | 10.156  | 2.3748 | 8.2793 | 9.7445    | 18.94   |
| 3.6077        | 7.5   | 6000 | 2.9283          | 10.3405 | 2.5197 | 8.3096 | 9.925     | 18.94   |
| 3.751         | 8.12  | 6500 | 2.9175          | 10.0746 | 2.4585 | 8.1791 | 9.6713    | 18.94   |
| 3.6265        | 8.75  | 7000 | 2.9167          | 10.1107 | 2.3335 | 8.163  | 9.6984    | 18.94   |
| 3.7021        | 9.38  | 7500 | 2.9146          | 10.4548 | 2.52   | 8.4699 | 9.9434    | 18.94   |
| 3.6102        | 10.0  | 8000 | 2.9121          | 10.3868 | 2.5204 | 8.4329 | 9.8992    | 18.94   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "google/mt5-small", "model-index": [{"name": "mt5-small-finetuned-test_76362_prefix_summarize", "results": []}]}
transformers pytorch mt5 text2text-generation generated_from_trainer base_model:google/mt5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us