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--- |
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license: apache-2.0 |
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base_model: google/mt5-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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- sacrebleu |
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model-index: |
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- name: mT5-TextSimp-LT-BatchSize8-lr5e-5 |
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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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# mT5-TextSimp-LT-BatchSize8-lr5e-5 |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0983 |
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- Rouge1: 0.6245 |
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- Rouge2: 0.4439 |
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- Rougel: 0.6142 |
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- Sacrebleu: 35.7192 |
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- Gen Len: 38.0501 |
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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: 8 |
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- eval_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:| |
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| 35.3898 | 0.96 | 200 | 27.6372 | 0.0019 | 0.0 | 0.0018 | 0.0003 | 512.0 | |
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| 3.5712 | 1.91 | 400 | 1.9615 | 0.0171 | 0.0 | 0.0167 | 0.0225 | 39.0501 | |
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| 0.6489 | 2.87 | 600 | 0.5638 | 0.0052 | 0.0 | 0.0051 | 0.0256 | 39.0501 | |
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| 0.6017 | 3.83 | 800 | 3.2823 | 0.2419 | 0.1287 | 0.2318 | 0.6457 | 130.3556 | |
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| 0.3784 | 4.78 | 1000 | 0.1340 | 0.5092 | 0.3277 | 0.4978 | 26.7005 | 38.0549 | |
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| 0.1521 | 5.74 | 1200 | 0.1092 | 0.5782 | 0.3973 | 0.5672 | 33.2443 | 38.0501 | |
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| 0.2096 | 6.7 | 1400 | 0.1001 | 0.6149 | 0.4342 | 0.6046 | 34.6518 | 38.0501 | |
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| 0.1719 | 7.66 | 1600 | 0.0983 | 0.6245 | 0.4439 | 0.6142 | 35.7192 | 38.0501 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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