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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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datasets: |
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- null |
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metrics: |
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- f1 |
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model-index: |
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- name: text-to-sparql-t5-small-2021-10-17_18-47 |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.2345714420080185 |
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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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# text-to-sparql-t5-small-2021-10-17_18-47 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5258 |
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- Gen Len: 19.0 |
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- P: 0.4582 |
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- R: 0.0278 |
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- F1: 0.2346 |
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- Score: 3.5848 |
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- Bleu-precisions: [82.57739877107295, 62.13358857503344, 48.43062944877681, 41.90172321318059] |
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- Bleu-bp: 0.0631 |
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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: 2e-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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- num_epochs: 1 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Gen Len | P | R | F1 | Score | Bleu-precisions | Bleu-bp | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:------:|:------:|:----------------------------------------------------------------------------:|:-------:| |
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| 0.7575 | 1.0 | 4807 | 0.5258 | 19.0 | 0.4582 | 0.0278 | 0.2346 | 3.5848 | [82.57739877107295, 62.13358857503344, 48.43062944877681, 41.90172321318059] | 0.0631 | |
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### Framework versions |
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- Transformers 4.10.0 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.13.3 |
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- Tokenizers 0.10.3 |
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