SFT-Cryptol-2.5-Coder-14B_v5
This model is a fine-tuned version of Qwen/Qwen2.5-Coder-14B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8053
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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.PAGED_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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8855 | 0.2974 | 20 | 0.9315 |
| 0.7895 | 0.5948 | 40 | 0.8817 |
| 0.6665 | 0.8922 | 60 | 0.8513 |
| 0.6695 | 1.1784 | 80 | 0.8323 |
| 0.5996 | 1.4758 | 100 | 0.8184 |
| 0.5776 | 1.7732 | 120 | 0.8093 |
| 0.611 | 2.0595 | 140 | 0.8067 |
| 0.4685 | 2.3569 | 160 | 0.8098 |
| 0.6223 | 2.6543 | 180 | 0.8054 |
| 0.5206 | 2.9517 | 200 | 0.8053 |
Framework versions
- PEFT 0.18.0
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1
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Model tree for j05hr3d/SFT-Cryptol-2.5-Coder-14B_v5
Base model
Qwen/Qwen2.5-14B
Finetuned
Qwen/Qwen2.5-Coder-14B
Finetuned
Qwen/Qwen2.5-Coder-14B-Instruct