loubnabnl/smollm-360M-instruct-add-basics-w-math

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smollm-360M-instruct-add-basics-w-math

This model is a fine-tuned version of HuggingFaceTB/SmolLM-360M on the HuggingFaceTB/Magpie-Pro-300K-Filtered-H4, the HuggingFaceTB/self-oss-instruct-sc2-H4, the HuggingFaceTB/OpenHermes-2.5-H4, the HuggingFaceTB/everyday-topics-MT-conversations-H4, the HuggingFaceTB/instruct-data-basics-H4 and the HuggingFaceTB/basic-math-MT-conversations-H4 datasets. It achieves the following results on the evaluation set:

• —Loss: 1.2017

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.001
• —trainbatchsize: 4
• —evalbatchsize: 4
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 8
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 128
• —totalevalbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 1

Training results

Framework versions

• —Transformers 4.42.3
• —Pytorch 2.1.2
• —Datasets 2.20.0
• —Tokenizers 0.19.1