---
library_name: peft
base_model: voidful/llm-codec
tags:
- base_model:adapter:voidful/llm-codec
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: llm-codec-fisher
  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. -->

# llm-codec-fisher

This model is a fine-tuned version of [voidful/llm-codec](https://huggingface.co/voidful/llm-codec) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3688

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 5.4036        | 1.0   | 21597 | 5.3688          |


### Framework versions

- PEFT 0.18.0
- Transformers 4.57.3
- Pytorch 2.9.0+cu129
- Datasets 4.4.1
- Tokenizers 0.22.1