metadata
license: llama3.2
library_name: transformers
tags:
- llama-factory
- freeze
- generated_from_trainer
base_model: unsloth/Llama-3.2-3B-Instruct
model-index:
- name: Llama-3.2-3B-Instruct-24-9-29
results: []
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Llama-3.2-3B-Instruct-24-9-29
This model is a fine-tuned version of unsloth/Llama-3.2-3B-Instruct on the lmsys_chat dataset. It achieves the following results on the evaluation set:
- Loss: 1.1817
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.256 | 0.0160 | 100 | 1.1817 |
| 1.236 | 0.0320 | 200 | 1.1817 |
| 1.2212 | 0.0480 | 300 | 1.1817 |
| 1.1804 | 0.0641 | 400 | 1.1817 |
| 1.2801 | 0.0801 | 500 | 1.1817 |
| 1.2232 | 0.0961 | 600 | 1.1817 |
| 1.2433 | 0.1121 | 700 | 1.1817 |
| 1.2231 | 0.1281 | 800 | 1.1817 |
| 1.2272 | 0.1441 | 900 | 1.1817 |
| 1.2843 | 0.1602 | 1000 | 1.1817 |
Framework versions
- Transformers 4.45.0
- Pytorch 2.4.0+cu124
- Datasets 2.19.1
- Tokenizers 0.20.0
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 23.70 |
| IFEval (0-Shot) | 73.32 |
| BBH (3-Shot) | 24.20 |
| MATH Lvl 5 (4-Shot) | 15.26 |
| GPQA (0-shot) | 3.24 |
| MuSR (0-shot) | 1.44 |
| MMLU-PRO (5-shot) | 24.76 |