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---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
- sacrebleu
model-index:
- name: mT5-TextSimp-LT-BatchSize4-lr5e-5
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-TextSimp-LT-BatchSize4-lr5e-5
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: 0.1611
- Rouge1: 0.46
- Rouge2: 0.2767
- Rougel: 0.4464
- Sacrebleu: 23.2936
- Gen Len: 39.0358
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 36.6446 | 0.48 | 200 | 31.2765 | 0.0004 | 0.0 | 0.0004 | 0.0003 | 512.0 |
| 11.5223 | 0.96 | 400 | 6.7786 | 0.0031 | 0.0 | 0.0031 | 0.0045 | 89.2816 |
| 2.2686 | 1.44 | 600 | 0.6729 | 0.0054 | 0.0 | 0.0053 | 0.0196 | 39.0501 |
| 0.7009 | 1.91 | 800 | 0.6529 | 0.0029 | 0.0 | 0.0027 | 0.0424 | 41.401 |
| 0.6213 | 2.39 | 1000 | 0.5630 | 0.0058 | 0.0002 | 0.0056 | 0.0201 | 39.0334 |
| 0.6435 | 2.87 | 1200 | 0.4697 | 0.0688 | 0.0084 | 0.0608 | 0.1156 | 39.0453 |
| 0.4154 | 3.35 | 1400 | 10.4655 | 0.2098 | 0.1219 | 0.2011 | 0.671 | 350.0334 |
| 0.6289 | 3.83 | 1600 | 1.9257 | 0.3176 | 0.1945 | 0.3072 | 3.6031 | 138.7494 |
| 3.5542 | 4.31 | 1800 | 0.8459 | 0.373 | 0.2029 | 0.3615 | 16.8305 | 59.8568 |
| 8.1736 | 4.78 | 2000 | 7.2350 | 0.3147 | 0.1815 | 0.3033 | 7.3572 | 289.1432 |
| 2.3987 | 5.26 | 2200 | 0.8361 | 0.3616 | 0.1903 | 0.3501 | 16.2229 | 61.0668 |
| 0.9853 | 5.74 | 2400 | 0.4219 | 0.3635 | 0.2004 | 0.3515 | 15.2744 | 46.494 |
| 0.3575 | 6.22 | 2600 | 0.3516 | 0.3796 | 0.2121 | 0.3687 | 13.6464 | 46.1623 |
| 0.4497 | 6.7 | 2800 | 0.2597 | 0.4392 | 0.2698 | 0.4263 | 18.9423 | 42.2697 |
| 0.2582 | 7.18 | 3000 | 0.1583 | 0.4442 | 0.2579 | 0.431 | 21.5533 | 38.1671 |
| 0.2629 | 7.66 | 3200 | 0.1611 | 0.46 | 0.2767 | 0.4464 | 23.2936 | 39.0358 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.4
- Tokenizers 0.13.3
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