metadata
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: HuggingFaceTB/SmolLM-360M-Instruct
datasets:
- generator
model-index:
- name: SmolLM_360M_Instruct_qlora_nf4-plaba
results: []
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