---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5_deed_sum_1
  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_deed_sum_1

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5951
- Rouge1: 0.0572
- Rouge2: 0.0
- Rougel: 0.0572
- Rougelsum: 0.0572
- Gen Len: 19.0

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 24.1526       | 1.0   | 375  | 15.7524         | 0.7082 | 0.0    | 0.6842 | 0.6883    | 12.0881 |
| 11.2879       | 2.0   | 750  | 13.1581         | 0.7082 | 0.0    | 0.6842 | 0.6883    | 12.3208 |
| 10.5585       | 3.0   | 1125 | 7.4334          | 0.7082 | 0.0    | 0.6842 | 0.6883    | 17.1384 |
| 2.9668        | 4.0   | 1500 | 6.5357          | 0.7487 | 0.0    | 0.7176 | 0.7257    | 19.0    |
| 3.7198        | 5.0   | 1875 | 2.1303          | 0.7487 | 0.0    | 0.7176 | 0.7257    | 19.0    |
| 1.3383        | 6.0   | 2250 | 1.8675          | 0.7487 | 0.0    | 0.7176 | 0.7257    | 19.0    |
| 3.4973        | 7.0   | 2625 | 1.6299          | 0.7487 | 0.0    | 0.7176 | 0.7257    | 18.8994 |
| 11.7006       | 8.0   | 3000 | 4.6990          | 0.7487 | 0.0    | 0.7176 | 0.7257    | 19.0    |
| 0.4529        | 9.0   | 3375 | 1.0729          | 0.7487 | 0.0    | 0.7176 | 0.7257    | 19.0    |
| 1.2783        | 10.0  | 3750 | 0.9424          | 0.7487 | 0.0    | 0.7176 | 0.7257    | 19.0    |
| 0.7953        | 11.0  | 4125 | 0.8889          | 1.0108 | 0.2013 | 0.892  | 0.9014    | 19.0    |
| 0.9359        | 12.0  | 4500 | 0.7996          | 1.1489 | 0.3019 | 0.9952 | 0.9877    | 19.0    |
| 0.5759        | 13.0  | 4875 | 0.7622          | 0.1572 | 0.1144 | 0.1572 | 0.1572    | 19.0    |
| 0.1533        | 14.0  | 5250 | 0.7068          | 0.2144 | 0.1144 | 0.1715 | 0.1715    | 19.0    |
| 0.4524        | 15.0  | 5625 | 0.6760          | 0.3145 | 0.2287 | 0.3145 | 0.3145    | 19.0    |
| 1.0126        | 16.0  | 6000 | 0.6627          | 0.0    | 0.0    | 0.0    | 0.0       | 19.0    |
| 0.1065        | 17.0  | 6375 | 0.6391          | 0.3145 | 0.2287 | 0.3145 | 0.3145    | 19.0    |
| 0.2096        | 18.0  | 6750 | 0.6419          | 0.2144 | 0.1144 | 0.2144 | 0.2144    | 19.0    |
| 0.5649        | 19.0  | 7125 | 0.6261          | 0.1572 | 0.1144 | 0.1572 | 0.1572    | 19.0    |
| 0.125         | 20.0  | 7500 | 0.6139          | 0.1572 | 0.1144 | 0.1572 | 0.1572    | 19.0    |
| 0.5511        | 21.0  | 7875 | 0.6057          | 0.3145 | 0.2287 | 0.3145 | 0.3145    | 19.0    |
| 0.0759        | 22.0  | 8250 | 0.6029          | 0.3145 | 0.2287 | 0.3145 | 0.3145    | 19.0    |
| 0.3491        | 23.0  | 8625 | 0.5995          | 0.3145 | 0.2287 | 0.3145 | 0.3145    | 19.0    |
| 0.3735        | 24.0  | 9000 | 0.5936          | 0.1572 | 0.1144 | 0.1572 | 0.1572    | 19.0    |
| 0.3451        | 25.0  | 9375 | 0.5951          | 0.0572 | 0.0    | 0.0572 | 0.0572    | 19.0    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0.dev20230811+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2