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---
license: gemma
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
- ipex
- GPU Max 1100
- Intel(R) Data Center GPU Max 1100
datasets:
- generator
base_model: google/gemma-2b
model-index:
- name: gemma-finetuning
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-finetuning
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1674
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training Hardware
Intel(R) Data Center GPU Max 1100
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 593
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.8606 | 0.82 | 100 | 2.5425 |
| 2.4479 | 1.64 | 200 | 2.3304 |
| 2.3077 | 2.46 | 300 | 2.2351 |
| 2.2398 | 3.28 | 400 | 2.1914 |
| 2.2083 | 4.1 | 500 | 2.1674 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.0.1a0+cxx11.abi
- Datasets 2.18.0
- Tokenizers 0.15.2 |