metadata
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: reject-sampling_8_MATH_training_short_CoT
results: []
reject-sampling_8_MATH_training_short_CoT
This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the reject-sampling_8_MATH_training_short_CoT dataset. It achieves the following results on the evaluation set:
- Loss: 0.1684
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: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 8
- total_eval_batch_size: 4
- 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
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1755 | 0.2551 | 100 | 0.1783 |
| 0.1688 | 0.5102 | 200 | 0.1753 |
| 0.1684 | 0.7653 | 300 | 0.1720 |
| 0.1183 | 1.0204 | 400 | 0.1734 |
| 0.1013 | 1.2755 | 500 | 0.1717 |
| 0.1174 | 1.5306 | 600 | 0.1697 |
| 0.1391 | 1.7857 | 700 | 0.1684 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3