minitron-4b-tulu-v2-mix
This model is a fine-tuned version of nvidia/Minitron-4B-Base on the allenai/tulu-v2-sft-mixture dataset. It achieves the following results on the evaluation set:
- Loss: 1.1978
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0088 | 5 | 1.1978 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.19.1
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Model tree for kykim0/minitron-4b-tulu-v2-mix
Base model
nvidia/Minitron-4B-Base