---
language:
- code
license: bigcode-openrail-m
datasets:
- bigcode/the-stack-dedup
- Vipitis/Shadertoys-fine
pipeline_tag: text-generation
tags:
- code
- shader
base_model: bigcode/santacoder
widget:
- text: void mainImage( out vec4 fragColor, in vec2 fragCoord )
  example_title: mainImage
  group: Shadertoy
model-index:
- name: santacoder-finetuned-the-stack-glsl
  results:
  - task:
      type: text-generation
      name: ShaderEval
    dataset:
      type: Vipitis/Shadertoys-fine
      name: Shadertoys-fine
      config: return_completion
      revision: 0.0.2
    metrics:
      - type: exact_match
        value: 0.567
        name: 300 samples, greedy decoding
        verified: false
      - type: exact_match
        value: 0.59749
        name: all samples, greedy decoding
        verified: false
---

[Santacoder](https://huggingface.co/bigcode/santacoder) finetuned on [Shadertoys-fine](https://huggingface.co/datasets/Vipitis/Shadertoys-fine) for 1000 steps with a batch size of 2 and full sequence length of 2048.
adapted finetuning script found [here](./train.py)

Try model in the [ShaderCoder](https://huggingface.co/spaces/Vipitis/ShaderCoder) demo space

### Finetuning parameters
```sh
python3 train.py --model_path "bigcode/santacoder" \
--dataset_name "Vipitis/Shadertoys-fine" \
--data_column "code" \
--split "train" \
--seq_length 2048 \
--max_steps 1000 \
--batch_size 2 \
--gradient_accumulation_steps 4 \
--learning_rate 5e-5 \
--num_warmup_steps 100 \
--eval_freq 100 \
--save_freq 100 \
--log_freq 1 \
--output_dir "checkpoint_dir" \
--no_fp16


```

Main purpose of this model is to explore if finetuning models improves performance on [ShaderEval](https://huggingface.co/spaces/Vipitis/ShaderEval), which reached 0.567 with 300 samples and 0.59749 on all samples.

### Disclaimer

While the train/test split is held out, there is a lot of data contamination. The model results can't be trusted for this simple benchmark.
Better tasks for the benchmark will be developed and tested against these models.

License carried over from model, however training data has an undefied license. Check details in [Shadertoys](https://huggingface.co/datasets/Vipitis/Shadertoys).