README.md

metadata

license: gemma
library_name: peft
tags:
  - trl
  - reward-trainer
  - generated_from_trainer
metrics:
  - accuracy
base_model: google/gemma-2b
model-index:
  - name: RM-TLDR_human_loraR64_-1_gemma2b_lr1.41e-05_bs2_g4
    results: []

RM-TLDR_human_loraR64_-1_gemma2b_lr1.41e-05_bs2_g4

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

• Loss: 0.6086
• Accuracy: 0.6816

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: 1.41e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5634	1.0	11168	0.6055	0.6788
0.5285	2.0	22336	0.6086	0.6816

Framework versions

• PEFT 0.9.0
• Transformers 4.38.2
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2