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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: EN_mt5-small_15_spider
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# EN_mt5-small_15_spider
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3864
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- Rouge2 Precision: 0.4106
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- Rouge2 Recall: 0.2578
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- Rouge2 Fmeasure: 0.2937
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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| No log | 1.0 | 438 | 3.8361 | 0.0003 | 0.0006 | 0.0002 |
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| 16.5932 | 2.0 | 876 | 1.5381 | 0.0031 | 0.0012 | 0.0016 |
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| 2.0998 | 3.0 | 1314 | 0.7401 | 0.0938 | 0.052 | 0.0569 |
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| 1.1309 | 4.0 | 1752 | 0.4827 | 0.267 | 0.1627 | 0.1791 |
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| 0.5166 | 5.0 | 2190 | 0.4313 | 0.3065 | 0.1922 | 0.2121 |
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| 0.3883 | 6.0 | 2628 | 0.4112 | 0.3387 | 0.219 | 0.2418 |
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| 0.3299 | 7.0 | 3066 | 0.3975 | 0.3758 | 0.2331 | 0.2624 |
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| 0.293 | 8.0 | 3504 | 0.3896 | 0.3759 | 0.2451 | 0.2713 |
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| 0.293 | 9.0 | 3942 | 0.3914 | 0.396 | 0.2504 | 0.2838 |
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| 0.2687 | 10.0 | 4380 | 0.3863 | 0.3948 | 0.2531 | 0.2851 |
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| 0.2537 | 11.0 | 4818 | 0.3877 | 0.3962 | 0.2542 | 0.2863 |
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| 0.2431 | 12.0 | 5256 | 0.3860 | 0.4096 | 0.2545 | 0.2909 |
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| 0.2331 | 13.0 | 5694 | 0.3872 | 0.403 | 0.2561 | 0.2909 |
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| 0.23 | 14.0 | 6132 | 0.3862 | 0.4082 | 0.2577 | 0.293 |
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| 0.225 | 15.0 | 6570 | 0.3864 | 0.4106 | 0.2578 | 0.2937 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.7.dev0
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- Tokenizers 0.13.3
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