metadata
library_name: transformers
license: other
base_model: meta-llama/Llama-3.1-8B
tags:
- llama-factory
- full
- generated_from_trainer
datasets:
- tulu3_category_loader
model-index:
- name: Llama-3.1-8B_tulu3_mixture_coding_full_adamw_ebs128_lr5e-06_wsd-cr0.4
results: []
Llama-3.1-8B_tulu3_mixture_coding_full_adamw_ebs128_lr5e-06_wsd-cr0.4
This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the tulu3_mixture_coding dataset. It achieves the following results on the evaluation set:
- Loss: 0.7736 This checkpoint was released alongside https://arxiv.org/abs/2509.11167.
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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: warmup_stable_decay
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8738 | 0.0909 | 100 | 0.8080 |
| 0.8557 | 0.1818 | 200 | 0.8015 |
| 0.8619 | 0.2726 | 300 | 0.7972 |
| 0.8201 | 0.3635 | 400 | 0.7945 |
| 0.8609 | 0.4544 | 500 | 0.7920 |
| 0.8175 | 0.5453 | 600 | 0.7903 |
| 0.8462 | 0.6361 | 700 | 0.7885 |
| 0.8307 | 0.7270 | 800 | 0.7850 |
| 0.8595 | 0.8179 | 900 | 0.7791 |
| 0.8116 | 0.9088 | 1000 | 0.7748 |
| 0.8221 | 0.9996 | 1100 | 0.7736 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.0