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---
license: gemma
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b
datasets:
- llama-duo/synth_coding_dataset_dedup
model-index:
- name: gemma2b-coding-gpt4o-100k
  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. -->

# gemma2b-coding-gpt4o-100k

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_coding_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6825

## 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: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.6871        | 0.9979 | 235  | 1.4013          |
| 0.6707        | 2.0    | 471  | 1.3993          |
| 0.6047        | 2.9979 | 706  | 1.4091          |
| 0.5773        | 4.0    | 942  | 1.4428          |
| 0.5548        | 4.9979 | 1177 | 1.4904          |
| 0.5409        | 6.0    | 1413 | 1.5480          |
| 0.5151        | 6.9979 | 1648 | 1.6102          |
| 0.4987        | 8.0    | 1884 | 1.6578          |
| 0.4875        | 8.9979 | 2119 | 1.6813          |
| 0.4904        | 9.9788 | 2350 | 1.6825          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1