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README.md
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---
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tags:
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- generated_from_trainer
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datasets:
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- odinsynth_sequence_dataset
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metrics:
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- accuracy
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model-index:
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- name: odinsynth_encoder_decoder_native_hf_test
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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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dataset:
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name: odinsynth_sequence_dataset
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type: odinsynth_sequence_dataset
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config: synthetic_surface
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split: validation
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args: synthetic_surface
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9332272780290561
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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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# odinsynth_encoder_decoder_native_hf_test
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This model is a fine-tuned version of [](https://huggingface.co/) on the odinsynth_sequence_dataset dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0533
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- Accuracy: 0.9332
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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: 3
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- eval_batch_size: 3
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- seed: 42
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- gradient_accumulation_steps: 200
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- total_train_batch_size: 600
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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: 20.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 6.5753 | 0.67 | 60 | 6.1666 | 0.0150 |
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| 2.5262 | 1.34 | 120 | 2.1713 | 0.9345 |
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| 0.2343 | 2.01 | 180 | 0.1787 | 0.9346 |
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| 0.0713 | 2.68 | 240 | 0.0686 | 0.9330 |
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| 0.0631 | 3.35 | 300 | 0.0621 | 0.9334 |
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| 0.0603 | 4.02 | 360 | 0.0594 | 0.9332 |
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| 0.0589 | 4.69 | 420 | 0.0583 | 0.9334 |
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| 0.0579 | 5.36 | 480 | 0.0572 | 0.9336 |
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| 0.0575 | 6.03 | 540 | 0.0566 | 0.9333 |
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| 0.0561 | 6.69 | 600 | 0.0562 | 0.9333 |
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| 0.0559 | 7.36 | 660 | 0.0559 | 0.9332 |
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| 0.0551 | 8.03 | 720 | 0.0556 | 0.9332 |
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| 0.0548 | 8.7 | 780 | 0.0552 | 0.9333 |
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| 0.0546 | 9.37 | 840 | 0.0550 | 0.9333 |
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| 0.0539 | 10.04 | 900 | 0.0547 | 0.9331 |
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| 0.0546 | 10.71 | 960 | 0.0544 | 0.9332 |
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| 0.0538 | 11.38 | 1020 | 0.0543 | 0.9335 |
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| 0.0534 | 12.05 | 1080 | 0.0540 | 0.9333 |
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| 0.0532 | 12.72 | 1140 | 0.0539 | 0.9334 |
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| 0.0525 | 13.39 | 1200 | 0.0538 | 0.9334 |
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| 0.0526 | 14.06 | 1260 | 0.0538 | 0.9331 |
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| 0.0527 | 14.73 | 1320 | 0.0536 | 0.9331 |
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| 0.0529 | 15.4 | 1380 | 0.0536 | 0.9331 |
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| 0.0526 | 16.07 | 1440 | 0.0535 | 0.9331 |
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| 0.0524 | 16.74 | 1500 | 0.0534 | 0.9333 |
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| 0.0516 | 17.41 | 1560 | 0.0534 | 0.9331 |
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| 0.0527 | 18.08 | 1620 | 0.0534 | 0.9332 |
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| 0.0521 | 18.74 | 1680 | 0.0533 | 0.9332 |
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| 0.0519 | 19.41 | 1740 | 0.0533 | 0.9332 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 2.0.0
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- Datasets 2.11.0
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- Tokenizers 0.11.0
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