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@@ -27,59 +27,4 @@ model-index:
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  - name: smollm2-1.7B-8k-mix7-ep2-v2
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  results: []
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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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-
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- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/loubnabnl/huggingface/runs/6rp7tpcv)
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- # smollm2-1.7B-8k-mix7-ep2-v2
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-
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- This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-1.7B-8k](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-8k) on the HuggingFaceTB/magpie-ultra-v1.0-filtered-400K-H4, the HuggingFaceTB/OpenHermes-2.5-H4-200k, the HuggingFaceTB/ifeval-like-data-36k-H4, the HuggingFaceTB/Numina-CoT-H4, the HuggingFaceTB/MetaMathQA-H4-200k, the HuggingFaceTB/self-oss-instruct-sc2-H4, the HuggingFaceTB/systemchats2.0-H4-short, the HuggingFaceTB/summarization-data-10k-H4, the HuggingFaceTB/everyday-conversations-llama3.1-2k, the HuggingFaceTB/apigen-smollm-trl-FC-H4, the HuggingFaceTB/smollm-v2-summarization, the HuggingFaceTB/smollm-v2-rewriting-50k-H4, the HuggingFaceTB/explore-instruct-rewrite-H4 and the HuggingFaceTB/LongAlign-16k-ctx-english-H4 datasets.
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- It achieves the following results on the evaluation set:
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- - Loss: 1.0630
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-
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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-
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- The following hyperparameters were used during training:
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- - learning_rate: 0.0003
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- - train_batch_size: 4
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- - eval_batch_size: 4
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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: 128
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- - total_eval_batch_size: 32
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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: 0.1
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- - num_epochs: 2
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:------:|:----:|:---------------:|
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- | 0.7442 | 0.9992 | 893 | 1.0789 |
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- | 0.6705 | 1.9983 | 1786 | 1.0630 |
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-
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-
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- ### Framework versions
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-
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- - Transformers 4.42.3
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- - Pytorch 2.1.2
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- - Datasets 2.20.0
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- - Tokenizers 0.19.1
 
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  - name: smollm2-1.7B-8k-mix7-ep2-v2
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  results: []
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  ---
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+ SFT only version of https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct