---
library_name: peft
license: other
base_model: google/gemma-2-9b-it
tags:
- base_model:adapter:google/gemma-2-9b-it
- llama-factory
- lora
- transformers
metrics:
- accuracy
pipeline_tag: text-generation
model-index:
- name: nli_P2_multi_n500_seed42
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# nli_P2_multi_n500_seed42

This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on the nli_multi_n500_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2139
- Accuracy: 0.9458
- Mcq Accuracy: 0.7311

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Mcq Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------------:|
| 0.0458        | 1.7751 | 500  | 0.1556          | 0.9427   | 0.7222       |


### Framework versions

- PEFT 0.18.1
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2