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README.md
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# smol-3b
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It achieves the following results on the evaluation set:
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- Loss: 10.6857
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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: 2e-05
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- gradient_accumulation_steps: 128
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- total_train_batch_size: 512
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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
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 11.2151 | 0.16 | 3 | 10.6857 |
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### Framework versions
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- Transformers 4.36.0.dev0
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- Pytorch 2.1.1+cu121
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- Datasets 2.14.6
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- Tokenizers 0.15.0
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## Training procedure
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### Framework versions
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- PEFT 0.6.1
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# smol-3b
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See how open weights instead of open source feel like!
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