metadata
license: gemma
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b
datasets:
- generator
model-index:
- name: gemma2b-summarize-gpt4o-2k
results: []
gemma2b-summarize-gpt4o-2k
This model is a fine-tuned version of google/gemma-2b on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 2.5693
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- total_eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.9969 | 1.0 | 5 | 3.1171 |
| 2.5079 | 2.0 | 10 | 2.8491 |
| 2.1709 | 3.0 | 15 | 2.7251 |
| 1.9297 | 4.0 | 20 | 2.6267 |
| 1.7591 | 5.0 | 25 | 2.5900 |
| 1.6527 | 6.0 | 30 | 2.5908 |
| 1.5938 | 7.0 | 35 | 2.5817 |
| 1.5589 | 8.0 | 40 | 2.5729 |
| 1.5434 | 9.0 | 45 | 2.5688 |
| 1.5362 | 10.0 | 50 | 2.5693 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1