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---
library_name: peft
license: apache-2.0
base_model: unsloth/SmolLM2-135M-Instruct
tags:
- unsloth
- trl
- sft
- generated_from_trainer
model-index:
- name: SmolLM2-135M-Instruct-TaiwanChat
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/pesi/SmolLM2-135M-Instruct-TaiwanChat_CLOUD/runs/9fnxruem)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/pesi/SmolLM2-135M-Instruct-TaiwanChat_CLOUD/runs/9fnxruem)
# SmolLM2-135M-Instruct-TaiwanChat

This model is a fine-tuned version of [unsloth/SmolLM2-135M-Instruct](https://huggingface.co/unsloth/SmolLM2-135M-Instruct) on an unknown dataset.

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 10
- training_steps: 60
- mixed_precision_training: Native AMP

### Framework versions

- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0