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---
license: gemma
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: google/gemma-7b
datasets:
- chansung/merge_summarize_dataset
model-index:
- name: gemma7b-summarize-11k
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-11k
This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the chansung/merge_summarize_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6219
## 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: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.8367 | 0.9907 | 53 | 2.7327 |
| 1.0189 | 2.0 | 107 | 2.3246 |
| 0.8788 | 2.9907 | 160 | 2.2786 |
| 0.8104 | 4.0 | 214 | 2.2754 |
| 0.7626 | 4.9907 | 267 | 2.3205 |
| 0.6665 | 6.0 | 321 | 2.3903 |
| 0.6015 | 6.9907 | 374 | 2.4630 |
| 0.5699 | 8.0 | 428 | 2.5837 |
| 0.5017 | 8.9907 | 481 | 2.6300 |
| 0.4969 | 9.9065 | 530 | 2.6219 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |