train_apps_1754507525
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the apps dataset. It achieves the following results on the evaluation set:
- Loss: 0.6625
- Num Input Tokens Seen: 880041568
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: 4
- eval_batch_size: 4
- seed: 123
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Input Tokens Seen |
|---|---|---|---|---|
| 0.7099 | 0.5000 | 13189 | 0.7341 | 44223136 |
| 0.6547 | 1.0000 | 26378 | 0.7023 | 87957952 |
| 0.6593 | 1.5001 | 39567 | 0.6880 | 131814656 |
| 0.5829 | 2.0001 | 52756 | 0.6804 | 175975840 |
| 0.596 | 2.5001 | 65945 | 0.6759 | 219881664 |
| 0.637 | 3.0001 | 79134 | 0.6724 | 263949472 |
| 0.6751 | 3.5001 | 92323 | 0.6702 | 307925280 |
| 0.5969 | 4.0002 | 105512 | 0.6682 | 352048320 |
| 0.5763 | 4.5002 | 118701 | 0.6669 | 396106880 |
| 0.6231 | 5.0002 | 131890 | 0.6656 | 440014752 |
| 0.7088 | 5.5002 | 145079 | 0.6649 | 484066880 |
| 0.6676 | 6.0002 | 158268 | 0.6641 | 528105600 |
| 0.8398 | 6.5002 | 171457 | 0.6636 | 572089824 |
| 0.5797 | 7.0003 | 184646 | 0.6631 | 616130592 |
| 0.7106 | 7.5003 | 197835 | 0.6630 | 660063168 |
| 0.6742 | 8.0003 | 211024 | 0.6627 | 704033600 |
| 0.7597 | 8.5003 | 224213 | 0.6626 | 747976128 |
| 0.6676 | 9.0003 | 237402 | 0.6625 | 792077152 |
| 0.575 | 9.5004 | 250591 | 0.6625 | 836063392 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
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Base model
meta-llama/Meta-Llama-3-8B-Instruct