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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-handwritten-io |
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metrics: |
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- accuracy |
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model-index: |
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- name: dalio-handwritten-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-handwritten-io |
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type: AlekseyKorshuk/dalio-handwritten-io |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.06143479984145858 |
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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-handwritten-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-handwritten-io dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3789 |
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- Accuracy: 0.0614 |
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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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| 2.9219 | 0.1 | 1 | 2.6484 | 0.0529 | |
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| 2.6938 | 0.2 | 2 | 2.6484 | 0.0529 | |
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| 2.6365 | 0.3 | 3 | 2.5508 | 0.0560 | |
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| 2.5088 | 0.4 | 4 | 2.5332 | 0.0562 | |
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| 2.7307 | 0.5 | 5 | 2.5176 | 0.0565 | |
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| 2.969 | 0.6 | 6 | 2.4941 | 0.0571 | |
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| 2.7283 | 0.7 | 7 | 2.4883 | 0.0567 | |
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| 2.6157 | 0.8 | 8 | 2.4766 | 0.0578 | |
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| 2.6406 | 0.9 | 9 | 2.4590 | 0.0583 | |
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| 2.5701 | 1.0 | 10 | 2.4375 | 0.0587 | |
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| 2.2017 | 1.1 | 11 | 2.4238 | 0.0587 | |
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| 2.0039 | 1.2 | 12 | 2.4219 | 0.0586 | |
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| 1.8981 | 1.3 | 13 | 2.4160 | 0.0589 | |
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| 1.7683 | 1.4 | 14 | 2.4160 | 0.0595 | |
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| 1.6746 | 1.5 | 15 | 2.4121 | 0.0600 | |
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| 1.8051 | 1.6 | 16 | 2.4102 | 0.0600 | |
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| 2.0457 | 1.7 | 17 | 2.4043 | 0.0602 | |
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| 1.8257 | 1.8 | 18 | 2.4004 | 0.0606 | |
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| 1.744 | 1.9 | 19 | 2.3887 | 0.0607 | |
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| 1.8232 | 2.0 | 20 | 2.3887 | 0.0607 | |
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| 1.4741 | 2.1 | 21 | 2.3828 | 0.0610 | |
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| 1.651 | 2.2 | 22 | 2.3770 | 0.0608 | |
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| 1.3732 | 2.3 | 23 | 2.3730 | 0.0610 | |
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| 1.3151 | 2.4 | 24 | 2.3730 | 0.0610 | |
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| 1.5302 | 2.5 | 25 | 2.3730 | 0.0610 | |
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| 1.2539 | 2.6 | 26 | 2.375 | 0.0612 | |
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| 1.6211 | 2.7 | 27 | 2.3770 | 0.0612 | |
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| 1.6047 | 2.8 | 28 | 2.3770 | 0.0613 | |
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| 1.1953 | 2.9 | 29 | 2.3789 | 0.0614 | |
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| 1.1621 | 3.0 | 30 | 2.3789 | 0.0614 | |
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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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