metadata
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b-it
model-index:
- name: ft-google-gemma-2b-it-qlora
results: []
ft-google-gemma-2b-it-qlora
This model is a fine-tuned version of google/gemma-2b-it on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.7958
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.0077 | 100.0 | 100 | 2.3782 |
0.0005 | 200.0 | 200 | 2.9807 |
0.0004 | 300.0 | 300 | 3.1002 |
0.0004 | 400.0 | 400 | 3.1932 |
0.0004 | 500.0 | 500 | 3.2895 |
0.0004 | 600.0 | 600 | 3.3658 |
0.0003 | 700.0 | 700 | 3.3978 |
0.0004 | 800.0 | 800 | 3.4260 |
0.0004 | 900.0 | 900 | 3.5341 |
0.0003 | 1000.0 | 1000 | 3.5190 |
0.0004 | 1100.0 | 1100 | 3.5536 |
0.0003 | 1200.0 | 1200 | 3.5967 |
0.0003 | 1300.0 | 1300 | 3.6020 |
0.0004 | 1400.0 | 1400 | 3.6300 |
0.0004 | 1500.0 | 1500 | 3.6133 |
0.0003 | 1600.0 | 1600 | 3.7128 |
0.0003 | 1700.0 | 1700 | 3.7430 |
0.0003 | 1800.0 | 1800 | 3.7682 |
0.0003 | 1900.0 | 1900 | 3.7548 |
0.0003 | 2000.0 | 2000 | 3.7958 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2