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--- |
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license: apache-2.0 |
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base_model: t5-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- arrow |
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model-index: |
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- name: text-to-sparql-t5-base-2024-09-01_11-28 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/padole/huggingface/runs/ca910scu) |
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# text-to-sparql-t5-base-2024-09-01_11-28 |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the arrow dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1292 |
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- Gen Len: 19.0 |
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- Bertscorer-p: 0.6002 |
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- Bertscorer-r: 0.1065 |
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- Bertscorer-f1: 0.3419 |
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- Sacrebleu-score: 6.1640 |
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- Sacrebleu-precisions: [92.31534063748829, 84.93160766667017, 79.6643621245387, 75.5827850229174] |
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- Bleu-bp: 0.0744 |
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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: 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 | Bertscorer-p | Bertscorer-r | Bertscorer-f1 | Sacrebleu-score | Sacrebleu-precisions | Bleu-bp | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:------------:|:-------------:|:---------------:|:--------------------------------------------------------------------------:|:-------:| |
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| 0.1458 | 1.0 | 4772 | 0.1292 | 19.0 | 0.6002 | 0.1065 | 0.3419 | 6.1640 | [92.31534063748829, 84.93160766667017, 79.6643621245387, 75.5827850229174] | 0.0744 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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