Llama-3.1-8B-Instruct-lora-finetuned-cont
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: 1.6096
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: 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.7031 | 1.0 | 153 | 1.6055 |
| 1.6803 | 2.0 | 306 | 1.6050 |
| 1.6407 | 3.0 | 459 | 1.6085 |
| 1.5938 | 4.0 | 612 | 1.6123 |
| 1.5797 | 5.0 | 765 | 1.6128 |
| 1.6056 | 6.0 | 918 | 1.6035 |
| 1.6003 | 7.0 | 1071 | 1.6040 |
| 1.6024 | 8.0 | 1224 | 1.6080 |
| 1.7389 | 9.0 | 1377 | 1.6052 |
| 1.684 | 10.0 | 1530 | 1.6096 |
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-cont
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct