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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- it5/datasets |
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metrics: |
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- rouge |
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model-index: |
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- name: it5-efficient-small-el32-qa-0.0003 |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: it5/datasets qa |
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type: it5/datasets |
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args: qa |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 74.2234 |
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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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# it5-efficient-small-el32-qa-0.0003 |
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This model is a fine-tuned version of [stefan-it/it5-efficient-small-el32](https://huggingface.co/stefan-it/it5-efficient-small-el32) on the it5/datasets qa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8225 |
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- Rouge1: 74.2234 |
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- Rouge2: 40.5909 |
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- Rougel: 74.1327 |
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- Rougelsum: 74.2081 |
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- Gen Len: 4.7055 |
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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: 0.0003 |
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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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- num_epochs: 7.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 1.1164 | 0.8 | 5000 | 0.8244 | 66.4678 | 35.3554 | 66.4543 | 66.4522 | 4.541 | |
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| 0.9097 | 1.59 | 10000 | 0.7299 | 70.0574 | 37.5535 | 69.9512 | 70.0084 | 4.5548 | |
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| 0.6637 | 2.39 | 15000 | 0.7314 | 72.0767 | 39.2263 | 72.0257 | 72.0473 | 4.703 | |
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| 0.5015 | 3.19 | 20000 | 0.7147 | 73.0185 | 39.9998 | 72.9347 | 72.9576 | 4.75 | |
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| 0.5101 | 3.99 | 25000 | 0.7055 | 73.7898 | 40.5481 | 73.7235 | 73.7901 | 4.8728 | |
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| 0.3903 | 4.78 | 30000 | 0.7442 | 74.0845 | 39.9841 | 74.0172 | 74.0635 | 4.5938 | |
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| 0.2993 | 5.58 | 35000 | 0.8184 | 73.8405 | 40.2569 | 73.7756 | 73.7972 | 4.7412 | |
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| 0.2227 | 6.38 | 40000 | 0.8278 | 74.0159 | 40.6403 | 73.9412 | 73.9722 | 4.742 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.0+cu102 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
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