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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Trelis/SmolLM-135M-Instruct-layer-pruned-90M-raw |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: 99-v9 |
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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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# 99-v9 |
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This model is a fine-tuned version of [Trelis/SmolLM-135M-Instruct-layer-pruned-90M-raw](https://huggingface.co/Trelis/SmolLM-135M-Instruct-layer-pruned-90M-raw) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7495 |
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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: 0.002 |
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- train_batch_size: 8 |
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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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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 64 |
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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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- lr_scheduler_warmup_ratio: 0.005 |
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- lr_scheduler_warmup_steps: 89 |
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- training_steps: 17894 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.6331 | 0.0500 | 894 | 0.6004 | |
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| 0.5667 | 0.0999 | 1788 | 0.5463 | |
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| 0.5423 | 0.1499 | 2682 | 0.5138 | |
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| 0.5749 | 0.1998 | 3576 | 0.7377 | |
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| 0.5378 | 0.2498 | 4470 | 0.7542 | |
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| 0.506 | 0.2998 | 5364 | 0.7902 | |
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| 0.5561 | 0.3497 | 6258 | 0.7810 | |
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| 0.5259 | 0.3997 | 7152 | 0.7914 | |
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| 0.5516 | 0.4496 | 8046 | 0.7611 | |
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| 0.5131 | 0.4996 | 8940 | 0.6860 | |
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| 0.5069 | 0.5496 | 9834 | 0.7247 | |
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| 0.4977 | 0.5995 | 10728 | 0.7375 | |
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| 0.4976 | 0.6495 | 11622 | 0.7436 | |
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| 0.5018 | 0.6995 | 12516 | 0.7520 | |
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| 0.537 | 0.7494 | 13410 | 0.7613 | |
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| 0.5018 | 0.7994 | 14304 | 0.6922 | |
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| 0.4891 | 0.8493 | 15198 | 0.7322 | |
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| 0.4808 | 0.8993 | 16092 | 0.7430 | |
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| 0.5231 | 0.9493 | 16986 | 0.7546 | |
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| 0.5103 | 0.9992 | 17880 | 0.7495 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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