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RichardErkhov/Trelis_-_99-base-checkpoints-v10-gguf

sourceHugging Faceupdated 2y agoView on Hugging Face
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Quantization made by Richard Erkhov.

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99-base-checkpoints-v10 - GGUF

  • —Model creator: https://huggingface.co/Trelis/
  • —Original model: https://huggingface.co/Trelis/99-base-checkpoints-v10/

Original model description: --- libraryname: transformers basemodel: Trelis/SmolLM-135M-layer-pruned-90M-raw tags:

  • —trl
  • —sft
  • —generatedfromtrainer model-index:
  • —name: 99-v10-base results: [] ---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

99-v10-base

This model is a fine-tuned version of Trelis/SmolLM-135M-layer-pruned-90M-raw on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.9658

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: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 8
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 512
  • —totalevalbatch_size: 128
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.01
  • —lrschedulerwarmup_steps: 19
  • —training_steps: 1951

Training results

Training LossEpochStepValidation Loss
0.72320.19993900.6950
0.78780.39987800.7088
0.56670.599711700.5514
0.53580.799615600.7882
0.47580.999519500.9658

Framework versions

  • —Transformers 4.44.2
  • —Pytorch 2.1.1+cu121
  • —Datasets 3.0.0
  • —Tokenizers 0.19.1