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metadata
license: gemma
library_name: peft
tags:
  - alignment-handbook
  - trl
  - sft
  - generated_from_trainer
base_model: google/gemma-2b
datasets:
  - llama-duo/synth_classification_dataset_dedup
model-index:
  - name: gemma2b-classification-gpt4o-100k
    results: []

gemma2b-classification-gpt4o-100k

This model is a fine-tuned version of google/gemma-2b on the llama-duo/synth_classification_dataset_dedup dataset. It achieves the following results on the evaluation set:

  • Loss: 2.8001

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: 15

Training results

Training Loss Epoch Step Validation Loss
1.4266 0.9969 159 1.9880
1.3029 2.0 319 1.9710
1.2414 2.9969 478 1.9794
1.2012 4.0 638 2.0134
1.1513 4.9969 797 2.0583
1.0951 6.0 957 2.1084
1.0414 6.9969 1116 2.2094
1.0041 8.0 1276 2.3043
0.9481 8.9969 1435 2.3989
0.9006 10.0 1595 2.5173
0.8626 10.9969 1754 2.6419
0.8351 12.0 1914 2.7331
0.8265 12.9969 2073 2.7838
0.8167 14.0 2233 2.7990
0.8075 14.9530 2385 2.8001

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1