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_r16_alpha64_lr5e-4_rsloratrue
    results: []

SmolLM-1.7B-Instruct-Summarization-Adapter_r16_alpha64_lr5e-4_rsloratrue

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: 1.7397

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: 0.0005
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
1.7159	1.0	1266	1.7397

Framework versions

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