---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen3-32B
tags:
- generated_from_trainer
model-index:
- name: Qwen3-32B-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-64D-1L-4H-256I
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Qwen3-32B-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-64D-1L-4H-256I

This model is a fine-tuned version of [Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4116

## 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: 0.001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- 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: 0.05
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| No log        | 0      | 0     | 3.0324          |
| 1.823         | 0.1280 | 500   | 1.7955          |
| 1.6508        | 0.2560 | 1000  | 1.6278          |
| 1.5539        | 0.3839 | 1500  | 1.5502          |
| 1.4746        | 0.5119 | 2000  | 1.4715          |
| 1.4543        | 0.6399 | 2500  | 1.4515          |
| 1.4434        | 0.7679 | 3000  | 1.4475          |
| 1.4379        | 0.8958 | 3500  | 1.4379          |
| 1.4354        | 1.0238 | 4000  | 1.4351          |
| 1.4319        | 1.1518 | 4500  | 1.4336          |
| 1.4317        | 1.2798 | 5000  | 1.4298          |
| 1.4285        | 1.4077 | 5500  | 1.4258          |
| 1.4251        | 1.5357 | 6000  | 1.4236          |
| 1.4247        | 1.6637 | 6500  | 1.4224          |
| 1.4208        | 1.7917 | 7000  | 1.4200          |
| 1.4183        | 1.9196 | 7500  | 1.4187          |
| 1.4178        | 2.0476 | 8000  | 1.4198          |
| 1.4163        | 2.1756 | 8500  | 1.4176          |
| 1.4183        | 2.3036 | 9000  | 1.4177          |
| 1.4175        | 2.4315 | 9500  | 1.4176          |
| 1.4144        | 2.5595 | 10000 | 1.4159          |
| 1.4147        | 2.6875 | 10500 | 1.4149          |
| 1.4168        | 2.8155 | 11000 | 1.4147          |
| 1.4147        | 2.9434 | 11500 | 1.4139          |
| 1.4141        | 3.0714 | 12000 | 1.4136          |
| 1.4116        | 3.1994 | 12500 | 1.4138          |
| 1.411         | 3.3274 | 13000 | 1.4133          |
| 1.4115        | 3.4553 | 13500 | 1.4125          |
| 1.4133        | 3.5833 | 14000 | 1.4124          |
| 1.4112        | 3.7113 | 14500 | 1.4122          |
| 1.41          | 3.8393 | 15000 | 1.4120          |
| 1.4134        | 3.9672 | 15500 | 1.4118          |
| 1.4115        | 4.0952 | 16000 | 1.4118          |
| 1.4139        | 4.2232 | 16500 | 1.4117          |
| 1.4134        | 4.3512 | 17000 | 1.4116          |
| 1.413         | 4.4791 | 17500 | 1.4116          |
| 1.41          | 4.6071 | 18000 | 1.4116          |
| 1.4108        | 4.7351 | 18500 | 1.4116          |
| 1.4124        | 4.8631 | 19000 | 1.4116          |
| 1.4122        | 4.9910 | 19500 | 1.4116          |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.1