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---
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
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