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---
library_name: peft
license: llama3
base_model: meta-llama/Meta-Llama-3-8B
tags:
- generated_from_trainer
model-index:
- name: results_llama_8b_fim
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results_llama_8b_fim
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0074
## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.3771 | 0.1145 | 100 | 1.0760 |
| 1.0804 | 0.2290 | 200 | 1.0491 |
| 1.1121 | 0.3434 | 300 | 1.0381 |
| 1.114 | 0.4579 | 400 | 1.0310 |
| 1.0847 | 0.5724 | 500 | 1.0264 |
| 1.0152 | 0.6869 | 600 | 1.0229 |
| 1.0289 | 0.8014 | 700 | 1.0203 |
| 1.0648 | 0.9159 | 800 | 1.0180 |
| 1.0885 | 1.0298 | 900 | 1.0156 |
| 1.0486 | 1.1442 | 1000 | 1.0122 |
| 1.1167 | 1.2587 | 1100 | 1.0108 |
| 1.0189 | 1.3732 | 1200 | 1.0098 |
| 1.0281 | 1.4877 | 1300 | 1.0090 |
| 1.0438 | 1.6022 | 1400 | 1.0084 |
| 1.0715 | 1.7167 | 1500 | 1.0079 |
| 1.0117 | 1.8311 | 1600 | 1.0076 |
| 1.024 | 1.9456 | 1700 | 1.0074 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 2.17.0
- Tokenizers 0.21.0 |