---
library_name: transformers
license: gemma
base_model: google/gemma-3-1b-it
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: gemma-3-1b-it_MED_NLI
  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. -->

# gemma-3-1b-it_MED_NLI

This model is a fine-tuned version of [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it) on the zero_shot dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0177

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- 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: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0331        | 0.1176 | 1000 | 0.0379          |
| 0.0299        | 0.2352 | 2000 | 0.0262          |
| 0.0251        | 0.3528 | 3000 | 0.0284          |
| 0.0213        | 0.4704 | 4000 | 0.0252          |
| 0.0264        | 0.5880 | 5000 | 0.0222          |
| 0.0183        | 0.7056 | 6000 | 0.0191          |
| 0.0171        | 0.8232 | 7000 | 0.0179          |
| 0.0185        | 0.9408 | 8000 | 0.0177          |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.0