long-context-dclm
This model is a fine-tuned version of open-sci/open-sci-ref-v0.02-1.7b-dclm-300B-4096 on the long_sft 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1.0
Training results
Framework versions
- Transformers 4.51.3
- Pytorch 2.8.0a0+5228986c39.nv25.06
- Datasets 3.6.0
- Tokenizers 0.21.4
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