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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-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: 0.0969 |
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- Rouge1: 0.6185 |
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- Rouge2: 0.4427 |
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- Rougel: 0.6087 |
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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 | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:| |
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| 32.3498 | 0.96 | 200 | 26.0719 | 0.0008 | 0.0 | 0.0008 | 512.0 | |
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| 5.8297 | 1.91 | 400 | 4.1306 | 0.0059 | 0.0 | 0.0058 | 45.0573 | |
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| 0.7087 | 2.87 | 600 | 0.6039 | 0.003 | 0.0 | 0.0029 | 39.0501 | |
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| 0.4166 | 3.83 | 800 | 0.1958 | 0.3954 | 0.2416 | 0.3823 | 39.0501 | |
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| 0.2193 | 4.78 | 1000 | 0.1172 | 0.5244 | 0.3536 | 0.514 | 38.0501 | |
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| 0.1371 | 5.74 | 1200 | 0.1029 | 0.5936 | 0.4122 | 0.5839 | 38.0501 | |
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| 0.1971 | 6.7 | 1400 | 0.0974 | 0.6077 | 0.4302 | 0.5984 | 38.0501 | |
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| 0.1653 | 7.66 | 1600 | 0.0969 | 0.6185 | 0.4427 | 0.6087 | 38.0501 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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