---
library_name: transformers
license: mit
base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 0be52334109f7de89ae483ae7934e6ff
  results: []
---

<!-- 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. -->

# 0be52334109f7de89ae483ae7934e6ff

This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) on the contemmcm/trec dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0305
- Data Size: 1.0
- Epoch Runtime: 162.3387
- Accuracy: 0.9625
- F1 Macro: 0.9522

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
| No log        | 0     | 0    | 24.0991         | 0         | 2.1170        | 0.1146   | 0.0434   |
| No log        | 1     | 170  | 25.0678         | 0.0078    | 3.2572        | 0.2896   | 0.1368   |
| No log        | 2     | 340  | 4.9327          | 0.0156    | 12.5939       | 0.5979   | 0.5061   |
| No log        | 3     | 510  | 1.9932          | 0.0312    | 26.1874       | 0.8396   | 0.7274   |
| No log        | 4     | 680  | 2.2692          | 0.0625    | 37.0808       | 0.8187   | 0.7867   |
| 0.2962        | 5     | 850  | 1.0584          | 0.125     | 51.6924       | 0.9417   | 0.9259   |
| 0.2962        | 6     | 1020 | 1.3186          | 0.25      | 72.8640       | 0.9229   | 0.9305   |
| 1.1754        | 7     | 1190 | 0.8004          | 0.5       | 111.3242      | 0.9563   | 0.9492   |
| 0.7022        | 8.0   | 1360 | 0.9660          | 1.0       | 178.2920      | 0.9583   | 0.9631   |
| 0.382         | 9.0   | 1530 | 1.1431          | 1.0       | 153.1476      | 0.9604   | 0.9644   |
| 0.5167        | 10.0  | 1700 | 0.9932          | 1.0       | 164.1829      | 0.9667   | 0.9692   |
| 0.3482        | 11.0  | 1870 | 1.0305          | 1.0       | 162.3387      | 0.9625   | 0.9522   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.1