---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- unsloth
- generated_from_trainer
base_model: unsloth/gemma-1.1-7b-it-bnb-4bit
model-index:
- name: gemma-QA-ViMMRC-Squad-v1.1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gemma-QA-ViMMRC-Squad-v1.1

This model is a fine-tuned version of [unsloth/gemma-1.1-7b-it-bnb-4bit](https://huggingface.co/unsloth/gemma-1.1-7b-it-bnb-4bit) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3372

## Model description

More information needed

## Intended uses & limitations

- **Prompt 1**: Given the following reference, create a question and a corresponding answer to the question: + [context]
- **Prompt 2**: Given the following reference, create a multiple-choice question and its corresponding answer: + [context]
  
## 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: 16
- eval_batch_size: 8
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8           | 0.2307 | 320  | 1.9584          |
| 0.4031        | 0.4614 | 640  | 2.0371          |
| 0.4           | 0.6921 | 960  | 2.1358          |
| 0.4           | 0.9229 | 1280 | 2.2552          |
| 0.2328        | 1.1536 | 1600 | 2.4241          |
| 0.2           | 1.3843 | 1920 | 2.5637          |
| 0.2           | 1.6150 | 2240 | 2.7250          |
| 0.1117        | 1.8457 | 2560 | 2.8899          |
| 0.1008        | 2.0764 | 2880 | 3.1551          |
| 0.0578        | 2.3071 | 3200 | 3.2185          |
| 0.0566        | 2.5379 | 3520 | 3.3025          |
| 0.0555        | 2.7686 | 3840 | 3.3309          |
| 0.0516        | 2.9993 | 4160 | 3.3372          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1