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---
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- llama-duo/synth_summarize_dataset_dedup
base_model: google/gemma-7b
model-index:
- name: gemma7b-summarize-claude3sonnet-64k
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. -->
# gemma7b-summarize-claude3sonnet-64k
This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the llama-duo/synth_summarize_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5547
## 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: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.1216 | 0.9967 | 150 | 2.5805 |
| 0.9828 | 2.0 | 301 | 2.5169 |
| 0.9157 | 2.9967 | 451 | 2.4836 |
| 0.8753 | 4.0 | 602 | 2.5011 |
| 0.8334 | 4.9967 | 752 | 2.4945 |
| 0.796 | 6.0 | 903 | 2.5317 |
| 0.7745 | 6.9967 | 1053 | 2.5436 |
| 0.7582 | 8.0 | 1204 | 2.5522 |
| 0.754 | 8.9967 | 1354 | 2.5504 |
| 0.7572 | 9.9668 | 1500 | 2.5547 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1 |