---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: google/gemma-2b
model-index:
- name: gemma-2b-prompt-dict_fix
  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-2b-prompt-dict_fix

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4486

## 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: 0.0004
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9304        | 0.38  | 100  | 1.1381          |
| 0.8056        | 0.75  | 200  | 1.0223          |
| 0.8532        | 1.13  | 300  | 0.9144          |
| 0.9387        | 1.5   | 400  | 0.8460          |
| 0.8744        | 1.88  | 500  | 0.7882          |
| 0.8939        | 2.26  | 600  | 0.7415          |
| 0.9265        | 2.63  | 700  | 0.7008          |
| 0.4869        | 3.01  | 800  | 0.6631          |
| 0.4609        | 3.38  | 900  | 0.6485          |
| 0.4909        | 3.76  | 1000 | 0.6063          |
| 0.5568        | 4.14  | 1100 | 0.5645          |
| 0.4727        | 4.51  | 1200 | 0.5412          |
| 0.5277        | 4.89  | 1300 | 0.5235          |
| 0.7115        | 5.26  | 1400 | 0.5122          |
| 0.5917        | 5.64  | 1500 | 0.4972          |
| 0.4643        | 6.02  | 1600 | 0.4777          |
| 0.275         | 6.39  | 1700 | 0.4750          |
| 0.4726        | 6.77  | 1800 | 0.4611          |
| 0.3297        | 7.14  | 1900 | 0.4496          |
| 0.3426        | 7.52  | 2000 | 0.4486          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2