baby-python-mistral-1L-tiny-lua-ft

This model is a fine-tuned version of nilq/baby-python-mistral-1L-tiny-base on the nilq/small-lua-stack dataset. This is the Lua model in the paper Tracking Universal Features Through Fine-Tuning and Model Merging. It achieves the following results on the evaluation set:

  • Loss: 2.4518
  • Accuracy: 0.4941

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: 2e-05
  • 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
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 1.0

Training results

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.2.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
Downloads last month
30
Safetensors
Model size
35.1M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for nilq/baby-python-mistral-1L-tiny-lua-ft

Finetuned
(2)
this model
Merges
1 model

Dataset used to train nilq/baby-python-mistral-1L-tiny-lua-ft

Collection including nilq/baby-python-mistral-1L-tiny-lua-ft

Evaluation results