meta-llama-Meta-Llama-3.1-8B-Instruct_playpen_SFT_DFINAL_VTrain
This model is a fine-tuned version of unsloth/meta-llama-3.1-8b-instruct-bnb-4bit on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2435
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: 4
- eval_batch_size: 8
- seed: 7331
- optimizer: Use adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- lr_scheduler_warmup_steps: 5
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2779 | 0.0565 | 100 | 0.3878 |
| 0.1818 | 0.1130 | 200 | 0.2886 |
| 0.1812 | 0.1695 | 300 | 0.2760 |
| 0.1508 | 0.2260 | 400 | 0.2683 |
| 0.1548 | 0.2825 | 500 | 0.2567 |
| 0.1572 | 0.3390 | 600 | 0.2579 |
| 0.1084 | 0.3955 | 700 | 0.2473 |
| 0.1426 | 0.4520 | 800 | 0.2611 |
| 0.1084 | 0.5085 | 900 | 0.2449 |
| 0.128 | 0.5650 | 1000 | 0.2485 |
| 0.1456 | 0.6215 | 1100 | 0.2378 |
| 0.1458 | 0.6780 | 1200 | 0.2403 |
| 0.1105 | 0.7345 | 1300 | 0.2387 |
| 0.1148 | 0.7910 | 1400 | 0.2446 |
| 0.0892 | 0.8475 | 1500 | 0.2407 |
| 0.0977 | 0.9040 | 1600 | 0.2397 |
| 0.1046 | 0.9605 | 1700 | 0.2435 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.21.0
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