metadata
license: gemma
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b
datasets:
- generator
model-index:
- name: gemma2b-summarize-claude3sonnet-128k
results: []
gemma2b-summarize-claude3sonnet-128k
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: 2.6928
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 |
---|---|---|---|
1.0192 | 1.0 | 402 | 2.4514 |
0.9424 | 2.0 | 804 | 2.4604 |
0.8955 | 3.0 | 1206 | 2.5064 |
0.8659 | 4.0 | 1608 | 2.5306 |
0.8359 | 5.0 | 2010 | 2.5706 |
0.7986 | 6.0 | 2412 | 2.6196 |
0.7778 | 7.0 | 2814 | 2.6583 |
0.7562 | 8.0 | 3216 | 2.6846 |
0.7563 | 9.0 | 3618 | 2.6927 |
0.7461 | 10.0 | 4020 | 2.6928 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1