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---
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
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