smollm-or-assignments
This model is a fine-tuned version of HuggingFaceTB/SmolLM-360M-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3428
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.3845 | 1.0959 | 200 | 2.3732 |
2.2959 | 2.1918 | 400 | 2.3428 |
Framework versions
- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for ambrosfitz/smollm-or-assignments
Base model
HuggingFaceTB/SmolLM-360M
Quantized
HuggingFaceTB/SmolLM-360M-Instruct