smollm-ft-llmhuman-example-adapter
This model is a fine-tuned version of HuggingFaceTB/SmolLM-360M-Instruct on the None dataset.
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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for aipib/smollm-ft-llmhuman-example-adapter
Base model
HuggingFaceTB/SmolLM-360M
Quantized
HuggingFaceTB/SmolLM-360M-Instruct