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incar-nlu-qwen1.5b
marcuschill1823/incar-nlu-qwen1.5b
incar-nlu-qwen1.5b is a machine learning model from marcuschill1823. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- May 30, 2026
- Updated
- Jun 4, 2026
- SHA
- e24debf5
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
incar-nlu-qwen1.5b
This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the incar_nlu dataset. It achieves the following results on the evaluation set:
- Loss: 0.2066
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.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: 0.03
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2474 | 0.32 | 200 | 0.2363 |
| 0.2228 | 0.64 | 400 | 0.2249 |
| 0.2337 | 0.96 | 600 | 0.2129 |
| 0.1525 | 1.28 | 800 | 0.2115 |
| 0.1601 | 1.6 | 1000 | 0.2109 |
| 0.1792 | 1.92 | 1200 | 0.2066 |
| 0.1158 | 2.24 | 1400 | 0.2169 |
| 0.1148 | 2.56 | 1600 | 0.2199 |
| 0.1132 | 2.88 | 1800 | 0.2198 |
Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.10.0+cu128
- Datasets 3.1.0
- Tokenizers 0.20.3
- Library
- peft
- License
- apache-2.0
- Created
- May 30, 2026
- Updated
- Jun 4, 2026