lora_0-5_3B-instruct
This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the gulaschnascher4000/stream-dataset-0-2, the identity-chatgulaschpt, the dolly_15k_de, the alpaca-gpt4_de, the ultrachat_de, the airoboros_de, the booksum_de, the dolphin_de, the evol_instruct_de, the dolly_15k_de and the oasst_de datasets. It achieves the following results on the evaluation set:
- Loss: 1.2895
Model description
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Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAFACTOR and the args are: scale_parameter=True, relative_step=True, warmup_init=True, lr=None
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 0.1
Training results
Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for gulaschnascher4000/lora_0-5_3B-instruct
Base model
meta-llama/Llama-3.2-3B-Instruct