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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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datasets: |
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- AlekseyKorshuk/dalio-all-io |
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metrics: |
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- accuracy |
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model-index: |
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- name: dalio-all-io-1.3b |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: AlekseyKorshuk/dalio-all-io |
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type: AlekseyKorshuk/dalio-all-io |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.05582538140677676 |
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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-all-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 the AlekseyKorshuk/dalio-all-io dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3652 |
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- Accuracy: 0.0558 |
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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: 1.0 |
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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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| 2.6543 | 0.03 | 1 | 2.6113 | 0.0513 | |
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| 2.6077 | 0.07 | 2 | 2.6113 | 0.0513 | |
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| 2.5964 | 0.1 | 3 | 2.5605 | 0.0519 | |
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| 2.7302 | 0.14 | 4 | 2.5234 | 0.0527 | |
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| 2.7 | 0.17 | 5 | 2.5078 | 0.0528 | |
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| 2.5674 | 0.21 | 6 | 2.4941 | 0.0532 | |
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| 2.6406 | 0.24 | 7 | 2.4883 | 0.0534 | |
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| 2.5315 | 0.28 | 8 | 2.4805 | 0.0536 | |
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| 2.7202 | 0.31 | 9 | 2.4727 | 0.0537 | |
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| 2.5144 | 0.34 | 10 | 2.4648 | 0.0536 | |
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| 2.4983 | 0.38 | 11 | 2.4512 | 0.0537 | |
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| 2.7029 | 0.41 | 12 | 2.4414 | 0.0539 | |
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| 2.5198 | 0.45 | 13 | 2.4336 | 0.0540 | |
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| 2.5706 | 0.48 | 14 | 2.4258 | 0.0545 | |
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| 2.5688 | 0.52 | 15 | 2.4180 | 0.0548 | |
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| 2.3793 | 0.55 | 16 | 2.4102 | 0.0552 | |
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| 2.4785 | 0.59 | 17 | 2.4043 | 0.0554 | |
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| 2.4688 | 0.62 | 18 | 2.3984 | 0.0553 | |
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| 2.5674 | 0.66 | 19 | 2.3984 | 0.0553 | |
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| 2.5054 | 0.69 | 20 | 2.3945 | 0.0554 | |
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| 2.452 | 0.72 | 21 | 2.3887 | 0.0555 | |
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| 2.5999 | 0.76 | 22 | 2.3828 | 0.0556 | |
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| 2.3665 | 0.79 | 23 | 2.3789 | 0.0556 | |
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| 2.6223 | 0.83 | 24 | 2.375 | 0.0557 | |
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| 2.3562 | 0.86 | 25 | 2.3711 | 0.0557 | |
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| 2.429 | 0.9 | 26 | 2.3691 | 0.0557 | |
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| 2.563 | 0.93 | 27 | 2.3672 | 0.0558 | |
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| 2.4573 | 0.97 | 28 | 2.3652 | 0.0558 | |
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| 2.4883 | 1.0 | 29 | 2.3652 | 0.0558 | |
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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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