qwen2.5-1.5b-diffusion-scientific-design
This model is a fine-tuned version of lamm-mit/qwen2.5-1.5b-diffusion-ultrachat on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.9131
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.05
- num_epochs: 20.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 57.7131 | 3.128 | 100 | 3.7250 |
| 56.7317 | 6.256 | 200 | 4.1247 |
| 59.6119 | 9.384 | 300 | 3.6308 |
| 62.2602 | 12.512 | 400 | 3.9451 |
| 62.9990 | 15.64 | 500 | 3.6218 |
| 60.6763 | 18.768 | 600 | 3.9414 |
| 52.4121 | 20.0 | 640 | 3.9131 |
Framework versions
- Transformers 5.14.1
- Pytorch 2.13.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2
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Base model
lamm-mit/qwen2.5-1.5b-diffusion-ultrachat