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SmolLM_360M_Instruct_qlora_nf4-plaba

This model is a fine-tuned version of HuggingFaceTB/SmolLM-360M-Instruct on the generator dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8521

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
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss
No log 0.8889 2 2.0708
No log 1.7778 4 2.0152
No log 2.6667 6 1.9361
No log 4.0 9 1.8851
1.9803 4.8889 11 1.8728
1.9803 5.7778 13 1.8640
1.9803 6.6667 15 1.8571
1.9803 8.0 18 1.8525
1.8574 8.8889 20 1.8521

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.0
  • Pytorch 2.1.0
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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