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--- |
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license: bigscience-bloom-rail-1.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bloom-560m-finetuned-the-stack-brainfuck |
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results: [] |
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widget: |
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- text: " |
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>+++++++++[<++++++++>-]<.>+++++++[<++++>-]<+.+++++++..+++.[-]>++++++++[<++++>-] |
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<.>+++++++++++[<++++++++>-]<-.--------.+++.-[.>>+>+<<<-]>>>" |
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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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# bloom-560m-finetuned-the-stack-brainfuck |
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This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2112 |
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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: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.3877 | 0.1 | 200 | 1.8023 | |
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| 1.2576 | 0.19 | 400 | 1.7121 | |
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| 1.1452 | 0.29 | 600 | 1.5469 | |
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| 1.1503 | 0.39 | 800 | 1.6261 | |
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| 1.0287 | 0.48 | 1000 | 1.5097 | |
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| 1.0118 | 0.58 | 1200 | 1.4398 | |
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| 1.0466 | 0.67 | 1400 | 1.4267 | |
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| 0.9531 | 0.77 | 1600 | 1.4130 | |
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| 0.8891 | 0.87 | 1800 | 1.4026 | |
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| 0.9163 | 0.96 | 2000 | 1.4003 | |
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| 0.7207 | 1.06 | 2200 | 1.3758 | |
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| 0.7041 | 1.16 | 2400 | 1.3364 | |
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| 0.7065 | 1.25 | 2600 | 1.3095 | |
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| 0.7316 | 1.35 | 2800 | 1.2959 | |
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| 0.6817 | 1.45 | 3000 | 1.2682 | |
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| 0.6926 | 1.54 | 3200 | 1.2567 | |
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| 0.6511 | 1.64 | 3400 | 1.2416 | |
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| 0.6819 | 1.73 | 3600 | 1.2263 | |
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| 0.6422 | 1.83 | 3800 | 1.2206 | |
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| 0.6392 | 1.93 | 4000 | 1.2112 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.5.1 |
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- Tokenizers 0.13.0 |
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