---
library_name: transformers
license: mit
base_model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: final_checkpoint
  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. -->

# final_checkpoint

This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4805

## 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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use adafactor and the args are:
No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.6773        | 0.0464 | 50   | 2.4460          |
| 0.7309        | 0.0929 | 100  | 0.7180          |
| 0.5965        | 0.1393 | 150  | 0.6000          |
| 0.5401        | 0.1857 | 200  | 0.5535          |
| 0.5055        | 0.2321 | 250  | 0.5285          |
| 0.4901        | 0.2786 | 300  | 0.5148          |
| 0.5266        | 0.3250 | 350  | 0.5047          |
| 0.4829        | 0.3714 | 400  | 0.4973          |
| 0.4825        | 0.4178 | 450  | 0.4922          |
| 0.508         | 0.4643 | 500  | 0.4886          |
| 0.503         | 0.5107 | 550  | 0.4858          |
| 0.514         | 0.5571 | 600  | 0.4835          |
| 0.492         | 0.6035 | 650  | 0.4822          |
| 0.4743        | 0.6500 | 700  | 0.4814          |
| 0.4942        | 0.6964 | 750  | 0.4809          |
| 0.4811        | 0.7428 | 800  | 0.4806          |
| 0.4645        | 0.7892 | 850  | 0.4805          |
| 0.4673        | 0.8357 | 900  | 0.4805          |
| 0.4933        | 0.8821 | 950  | 0.4805          |
| 0.5026        | 0.9285 | 1000 | 0.4805          |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0