---
tags:
- generated_from_trainer
datasets:
- nilq/small-lua-stack
metrics:
- accuracy
model-index:
- name: lua-mistral-1L-mini
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: nilq/small-lua-stack
      type: nilq/small-lua-stack
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4208221928842605
---

# lua-mistral-1L-mini

This model is a mini single-layer Mistral model pre-trained on on the `nilq/small-lua-stack` dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0245
- Accuracy: 0.4208

## Model description

This model might contain some very simple model of Lua.

## Intended uses & limitations

Let's see if we can find some interesting stuff inside this model.

## Training and evaluation data

Trained on the Lua subset of The Stack.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0006
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0

### Training results

- Loss: 3.016

### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2