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e22vvb
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EN_mrm8488_spider

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t5
text2text-generation
Generated from Trainer
text-generation-inference
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Files changed (7) hide show
  1. README.md +72 -0
  2. generation_config.json +7 -0
  3. runs/Jan22_12-45-34_munich/events.out.tfevents.1705902362.munich.473921.0 +2 -2
  4. special_tokens_map.json +107 -0
  5. spiece.model +3 -0
  6. tokenizer.json +0 -0
  7. tokenizer_config.json +113 -0
README.md ADDED
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: EN_mrm8488_spider
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+ results: []
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+ ---
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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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+
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+ # EN_mrm8488_spider
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+
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+ This model is a fine-tuned version of [mrm8488/t5-small-finetuned-wikiSQL](https://huggingface.co/mrm8488/t5-small-finetuned-wikiSQL) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1002
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+ - Rouge2 Precision: 0.0364
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+ - Rouge2 Recall: 0.0288
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+ - Rouge2 Fmeasure: 0.0266
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 16
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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: 15
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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+ | No log | 1.0 | 438 | 0.4103 | 0.3532 | 0.1547 | 0.194 |
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+ | 0.9639 | 2.0 | 876 | 0.2544 | 0.189 | 0.086 | 0.1038 |
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+ | 0.3388 | 3.0 | 1314 | 0.1954 | 0.1365 | 0.0641 | 0.0768 |
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+ | 0.2255 | 4.0 | 1752 | 0.1614 | 0.0644 | 0.0377 | 0.0407 |
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+ | 0.1673 | 5.0 | 2190 | 0.1412 | 0.0675 | 0.0443 | 0.0467 |
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+ | 0.1356 | 6.0 | 2628 | 0.1344 | 0.0528 | 0.0361 | 0.0366 |
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+ | 0.1148 | 7.0 | 3066 | 0.1255 | 0.0476 | 0.0333 | 0.0338 |
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+ | 0.0998 | 8.0 | 3504 | 0.1167 | 0.0513 | 0.0389 | 0.0374 |
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+ | 0.0998 | 9.0 | 3942 | 0.1107 | 0.0619 | 0.0447 | 0.0439 |
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+ | 0.088 | 10.0 | 4380 | 0.1092 | 0.0529 | 0.0412 | 0.0384 |
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+ | 0.0816 | 11.0 | 4818 | 0.1047 | 0.0478 | 0.0358 | 0.0334 |
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+ | 0.0742 | 12.0 | 5256 | 0.1015 | 0.0386 | 0.0306 | 0.028 |
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+ | 0.071 | 13.0 | 5694 | 0.1018 | 0.0384 | 0.0301 | 0.0281 |
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+ | 0.0674 | 14.0 | 6132 | 0.1004 | 0.0344 | 0.0279 | 0.0256 |
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+ | 0.0674 | 15.0 | 6570 | 0.1002 | 0.0364 | 0.0288 | 0.0266 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.7.dev0
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+ - Tokenizers 0.13.3
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