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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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model-index: |
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- name: mT5-TextSimp-LT-BatchSize12-lr1e-4 |
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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-BatchSize12-lr1e-4 |
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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: 0.1611 |
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- Rouge1: 0.4599 |
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- Rouge2: 0.2777 |
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- Rougel: 0.4471 |
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- Gen Len: 39.0358 |
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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: 4 |
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- eval_batch_size: 4 |
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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 | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:| |
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| 36.6446 | 0.48 | 200 | 31.2765 | 0.0004 | 0.0 | 0.0004 | 512.0 | |
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| 11.5223 | 0.96 | 400 | 6.7786 | 0.003 | 0.0 | 0.0031 | 89.2816 | |
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| 2.2686 | 1.44 | 600 | 0.6729 | 0.0053 | 0.0 | 0.0053 | 39.0501 | |
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| 0.7009 | 1.91 | 800 | 0.6529 | 0.0029 | 0.0 | 0.0027 | 41.401 | |
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| 0.6213 | 2.39 | 1000 | 0.5630 | 0.0057 | 0.0002 | 0.0056 | 39.0334 | |
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| 0.6435 | 2.87 | 1200 | 0.4697 | 0.0685 | 0.0084 | 0.0611 | 39.0453 | |
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| 0.4154 | 3.35 | 1400 | 10.4655 | 0.2093 | 0.1217 | 0.2006 | 350.0334 | |
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| 0.6289 | 3.83 | 1600 | 1.9257 | 0.317 | 0.1946 | 0.3064 | 138.7494 | |
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| 3.5542 | 4.31 | 1800 | 0.8459 | 0.3735 | 0.204 | 0.3613 | 59.8568 | |
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| 8.1736 | 4.78 | 2000 | 7.2350 | 0.3144 | 0.1819 | 0.3037 | 289.1432 | |
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| 2.3987 | 5.26 | 2200 | 0.8361 | 0.3621 | 0.1911 | 0.351 | 61.0668 | |
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| 0.9853 | 5.74 | 2400 | 0.4219 | 0.3634 | 0.2008 | 0.352 | 46.494 | |
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| 0.3575 | 6.22 | 2600 | 0.3516 | 0.3805 | 0.2128 | 0.3689 | 46.1623 | |
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| 0.4497 | 6.7 | 2800 | 0.2597 | 0.4388 | 0.2698 | 0.4269 | 42.2697 | |
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| 0.2582 | 7.18 | 3000 | 0.1583 | 0.4444 | 0.2587 | 0.4316 | 38.1671 | |
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| 0.2629 | 7.66 | 3200 | 0.1611 | 0.4599 | 0.2777 | 0.4471 | 39.0358 | |
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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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