Llama-3.1-8B-Instruct-lora-finetuned-fol
This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2384
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
- optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.1628 | 1.0 | 1211 | 0.2254 |
0.1627 | 2.0 | 2422 | 0.2023 |
0.1264 | 3.0 | 3633 | 0.1923 |
0.0973 | 4.0 | 4844 | 0.1930 |
0.0934 | 5.0 | 6055 | 0.1903 |
0.0845 | 6.0 | 7266 | 0.1922 |
0.0716 | 7.0 | 8477 | 0.2055 |
0.0679 | 8.0 | 9688 | 0.2116 |
0.0714 | 9.0 | 10899 | 0.2072 |
0.062 | 10.0 | 12110 | 0.2181 |
0.0649 | 11.0 | 13321 | 0.2182 |
0.0589 | 12.0 | 14532 | 0.2262 |
0.0614 | 13.0 | 15743 | 0.2226 |
0.0645 | 14.0 | 16954 | 0.2239 |
0.0566 | 15.0 | 18165 | 0.2384 |
Framework versions
- PEFT 0.10.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 2.19.0
- Tokenizers 0.21.0
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Model tree for jhkim64/Llama-3.1-8B-Instruct-lora-finetuned-fol
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct