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--- |
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license: apache-2.0 |
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base_model: HuggingFaceTB/SmolLM-360M |
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tags: |
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- alignment-handbook |
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- trl |
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- sft |
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- generated_from_trainer |
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- trl |
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- sft |
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- alignment-handbook |
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- generated_from_trainer |
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datasets: |
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- HuggingFaceTB/everyday-topics-MT-conversations-H4 |
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- HuggingFaceTB/instruct-data-basics-H4 |
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model-index: |
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- name: smollm-350M-instruct-add-basics-only |
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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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[<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/6sdxeci4) |
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# smollm-350M-instruct-add-basics-only |
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This model is a fine-tuned version of [HuggingFaceTB/SmolLM-360M](https://huggingface.co/HuggingFaceTB/SmolLM-360M) on the HuggingFaceTB/everyday-topics-MT-conversations-H4 and the HuggingFaceTB/instruct-data-basics-H4 datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4730 |
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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: 0.001 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.2577 | 0.5714 | 1 | 2.2421 | |
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| 2.2317 | 1.7143 | 3 | 2.2371 | |
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| 2.8729 | 2.8571 | 5 | 1.4730 | |
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### Framework versions |
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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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