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---
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
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