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---
license: other
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: deepseek-ai/deepseek-coder-1.3b-base
datasets:
- generator
model-index:
- name: hyperparam-rust-lora-32-6-epoch
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. -->
# hyperparam-rust-lora-32-6-epoch
This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4341
## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- lr_scheduler_warmup_steps: 1
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7587 | 0.3 | 25 | 0.5450 |
| 0.4998 | 0.59 | 50 | 0.4922 |
| 0.4682 | 0.89 | 75 | 0.4734 |
| 0.4551 | 1.18 | 100 | 0.4632 |
| 0.4375 | 1.48 | 125 | 0.4563 |
| 0.4389 | 1.77 | 150 | 0.4506 |
| 0.4327 | 2.07 | 175 | 0.4460 |
| 0.4245 | 2.37 | 200 | 0.4429 |
| 0.4129 | 2.66 | 225 | 0.4406 |
| 0.4188 | 2.96 | 250 | 0.4383 |
| 0.41 | 3.25 | 275 | 0.4374 |
| 0.413 | 3.55 | 300 | 0.4360 |
| 0.4113 | 3.84 | 325 | 0.4351 |
| 0.408 | 4.14 | 350 | 0.4347 |
| 0.4075 | 4.43 | 375 | 0.4345 |
| 0.4026 | 4.73 | 400 | 0.4343 |
| 0.4084 | 5.03 | 425 | 0.4341 |
| 0.4089 | 5.32 | 450 | 0.4341 |
| 0.4035 | 5.62 | 475 | 0.4341 |
| 0.4039 | 5.91 | 500 | 0.4341 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2