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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-4k
  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-4k

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: 3.0527

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 21.1609       | 1.0   | 10   | 12.3637         |
| 14.2403       | 2.0   | 20   | 7.7626          |
| 12.4548       | 3.0   | 30   | 6.8741          |
| 8.6478        | 4.0   | 40   | 6.1412          |
| 3.1923        | 5.0   | 50   | 4.4401          |
| 1.9614        | 6.0   | 60   | 3.3292          |
| 1.692         | 7.0   | 70   | 3.1272          |
| 1.5661        | 8.0   | 80   | 3.0726          |
| 1.5417        | 9.0   | 90   | 3.0536          |
| 1.5287        | 10.0  | 100  | 3.0527          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1