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SmolLM-1.7B-Instruct-Summarization-Adapter_r32_alpha64_lr3e-4_rslorafalse

PEFT
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trl
sft
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metadata
base_model: HuggingFaceTB/SmolLM-1.7B-Instruct
library_name: peft
license: apache-2.0
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: SmolLM-1.7B-Instruct-Summarization-Adapter_r32_alpha64_lr3e-4_rslorafalse
    results: []

SmolLM-1.7B-Instruct-Summarization-Adapter_r32_alpha64_lr3e-4_rslorafalse

This model is a fine-tuned version of HuggingFaceTB/SmolLM-1.7B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7541

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: 0.0003
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
1.7291 1.0 1266 1.7541

Framework versions

  • PEFT 0.13.2
  • Transformers 4.45.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.1