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--- |
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tags: |
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- masked-auto-encoding |
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- generated_from_trainer |
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model-index: |
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- name: pixel-barec-pretrain |
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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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# pixel-barec-pretrain |
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This model is a fine-tuned version of [bensapir/pixel-barec-pretrain](https://huggingface.co/bensapir/pixel-barec-pretrain) on the wikipedia + bookcorpus dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6179 |
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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: 9.375e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.5 |
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- training_steps: 200000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:------:|:---------------:| |
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| 0.8164 | 11.19 | 10000 | 0.7569 | |
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| 0.7702 | 22.37 | 20000 | 0.7498 | |
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| 0.7668 | 33.56 | 30000 | 0.7477 | |
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| 0.7655 | 44.74 | 40000 | 0.7451 | |
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| 0.7653 | 27.98 | 50000 | 0.7479 | |
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| 0.7648 | 33.58 | 60000 | 0.7448 | |
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| 0.7645 | 39.17 | 70000 | 0.7464 | |
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| 0.7642 | 44.77 | 80000 | 0.7450 | |
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| 0.7636 | 50.36 | 90000 | 0.7427 | |
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| 0.7602 | 55.96 | 100000 | 0.7262 | |
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| 0.7279 | 61.56 | 110000 | 0.6972 | |
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| 0.6981 | 67.15 | 120000 | 0.6809 | |
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| 0.6781 | 72.75 | 130000 | 0.6643 | |
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| 0.6612 | 78.34 | 140000 | 0.6534 | |
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| 0.6483 | 83.94 | 150000 | 0.6426 | |
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| 0.6389 | 89.54 | 160000 | 0.6357 | |
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| 0.6318 | 95.13 | 170000 | 0.6320 | |
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| 0.6261 | 100.73 | 180000 | 0.6280 | |
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| 0.6214 | 106.32 | 190000 | 0.6200 | |
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| 0.6177 | 111.92 | 200000 | 0.6200 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 2.5.1 |
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- Datasets 2.1.1.dev0 |
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- Tokenizers 0.21.1 |
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