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ondevicellm/tinyllama_moe_sft_ultrachat200k_v2

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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tinyllamamoesftultrachat200kv2

This model is a fine-tuned version of ondevicellm/tinyllama_moe on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.1593

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: 2e-05
  • —trainbatchsize: 16
  • —evalbatchsize: 8
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 4
  • —gradientaccumulationsteps: 2
  • —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

Training LossEpochStepValidation Loss
1.3360.091001.3140
1.24260.182001.2376
1.20830.263001.2100
1.18620.354001.1934
1.15670.445001.1820
1.17770.536001.1737
1.16660.617001.1677
1.15310.78001.1636
1.15250.799001.1610
1.13960.8810001.1596
1.16810.9611001.1593

Framework versions

  • —Transformers 4.36.2
  • —Pytorch 2.1.2+cu118
  • —Datasets 2.14.6
  • —Tokenizers 0.15.0