AlekseyKorshuk
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README.md
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---
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license: other
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: dalio-synthetic-io-1.3b
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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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# dalio-synthetic-io-1.3b
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This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5957
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- Accuracy: 0.0624
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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: 3e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 16
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- total_eval_batch_size: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- num_epochs: 3.0
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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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| 2.6941 | 0.05 | 1 | 2.6543 | 0.0622 |
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| 2.6914 | 0.11 | 2 | 2.6543 | 0.0622 |
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| 2.6003 | 0.16 | 3 | 2.6016 | 0.0627 |
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| 2.5603 | 0.21 | 4 | 2.5703 | 0.0627 |
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| 2.6072 | 0.26 | 5 | 2.5508 | 0.0630 |
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| 2.5444 | 0.32 | 6 | 2.5469 | 0.0628 |
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| 2.4467 | 0.37 | 7 | 2.5508 | 0.0629 |
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| 2.5452 | 0.42 | 8 | 2.5508 | 0.0629 |
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| 2.6128 | 0.47 | 9 | 2.5449 | 0.0631 |
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| 2.4568 | 0.53 | 10 | 2.5391 | 0.0627 |
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| 2.5098 | 0.58 | 11 | 2.5352 | 0.0628 |
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| 2.6047 | 0.63 | 12 | 2.5234 | 0.0631 |
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| 2.5022 | 0.68 | 13 | 2.5156 | 0.0630 |
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| 2.605 | 0.74 | 14 | 2.5078 | 0.0633 |
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| 2.6055 | 0.79 | 15 | 2.5020 | 0.0634 |
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| 2.5061 | 0.84 | 16 | 2.4961 | 0.0632 |
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| 2.4348 | 0.89 | 17 | 2.4902 | 0.0631 |
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| 2.6284 | 0.95 | 18 | 2.4883 | 0.0632 |
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| 2.5574 | 1.0 | 19 | 2.4863 | 0.0631 |
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| 2.0814 | 1.05 | 20 | 2.4844 | 0.0633 |
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| 2.0636 | 1.11 | 21 | 2.4844 | 0.0635 |
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| 1.9459 | 1.16 | 22 | 2.4844 | 0.0635 |
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| 2.0527 | 1.21 | 23 | 2.4883 | 0.0634 |
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| 1.8881 | 1.26 | 24 | 2.4961 | 0.0635 |
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| 1.8668 | 1.32 | 25 | 2.5117 | 0.0636 |
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| 2.0375 | 1.37 | 26 | 2.5293 | 0.0636 |
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| 1.9402 | 1.42 | 27 | 2.5449 | 0.0632 |
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| 1.6086 | 1.47 | 28 | 2.5586 | 0.0633 |
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| 1.8185 | 1.53 | 29 | 2.5645 | 0.0632 |
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| 1.7324 | 1.58 | 30 | 2.5605 | 0.0630 |
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| 1.9285 | 1.63 | 31 | 2.5527 | 0.0628 |
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| 1.8031 | 1.68 | 32 | 2.5449 | 0.0631 |
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| 1.7321 | 1.74 | 33 | 2.5352 | 0.0630 |
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| 1.7802 | 1.79 | 34 | 2.5254 | 0.0631 |
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| 2.0637 | 1.84 | 35 | 2.5156 | 0.0632 |
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| 1.8159 | 1.89 | 36 | 2.5078 | 0.0633 |
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| 1.7142 | 1.95 | 37 | 2.5039 | 0.0634 |
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| 1.8793 | 2.0 | 38 | 2.5 | 0.0634 |
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| 1.6914 | 2.05 | 39 | 2.5020 | 0.0636 |
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| 1.411 | 2.11 | 40 | 2.5039 | 0.0639 |
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| 1.4182 | 2.16 | 41 | 2.5098 | 0.0639 |
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| 1.6223 | 2.21 | 42 | 2.5176 | 0.0638 |
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| 1.623 | 2.26 | 43 | 2.5273 | 0.0634 |
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| 1.5748 | 2.32 | 44 | 2.5371 | 0.0634 |
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| 1.7166 | 2.37 | 45 | 2.5469 | 0.0631 |
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| 1.3432 | 2.42 | 46 | 2.5566 | 0.0630 |
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| 1.5325 | 2.47 | 47 | 2.5645 | 0.0631 |
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| 1.5076 | 2.53 | 48 | 2.5723 | 0.0629 |
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| 1.6636 | 2.58 | 49 | 2.5781 | 0.0627 |
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| 1.2897 | 2.63 | 50 | 2.5840 | 0.0627 |
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| 1.4559 | 2.68 | 51 | 2.5879 | 0.0627 |
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| 1.3904 | 2.74 | 52 | 2.5898 | 0.0627 |
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| 1.4961 | 2.79 | 53 | 2.5918 | 0.0626 |
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| 1.5276 | 2.84 | 54 | 2.5938 | 0.0625 |
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| 1.3479 | 2.89 | 55 | 2.5957 | 0.0625 |
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| 1.4094 | 2.95 | 56 | 2.5957 | 0.0624 |
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| 1.5486 | 3.0 | 57 | 2.5957 | 0.0624 |
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### Framework versions
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- Transformers 4.25.0.dev0
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- Pytorch 1.12.1+cu113
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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