smollm-1.7B-v2-magpie-ultra-ifeval-OH-200k-true
This model is a fine-tuned version of HuggingFaceTB/SmolLM2-1.7B-final on the HuggingFaceTB/magpie-ultra-v1.0-filtered-600K-H4, the HuggingFaceTB/ifeval-like-data-H4 and the HuggingFaceTB/OpenHermes-2.5-H4-200k datasets. It achieves the following results on the evaluation set:
- Loss: 0.7543
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: 0.1
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.7431 | 0.9999 | 3736 | 0.7543 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for loubnabnl/smollm-1.7B-v2-magpie-ultra-ifeval-OH-200k-true
Base model
HuggingFaceTB/SmolLM2-1.7B-final