SomlLm-360M-Ko-Instruct
This model is a fine-tuned version of HuggingFaceTB/SmolLM-360M-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1516
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: 2e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 96
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1401 | 0.9993 | 1316 | 1.1516 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for CarrotAI/SmolLm-360M-Ko-Instruct
Base model
HuggingFaceTB/SmolLM-360M
Quantized
HuggingFaceTB/SmolLM-360M-Instruct