learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Auc
0.7096	1.0	25	0.6882	0.56	0.5191
0.6851	2.0	50	0.6858	0.56	0.5199
0.6961	3.0	75	0.6859	0.56	0.5463
0.6915	4.0	100	0.6858	0.56	0.5548
0.6936	5.0	125	0.6859	0.56	0.5548

Framework versions

Transformers 5.8.0
Pytorch 2.11.0+cu130
Datasets 4.8.5
Tokenizers 0.22.2

Generated by ML Intern

This model repository was generated by ML Intern, an agent for machine learning research and development on the Hugging Face Hub.

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Source code: https://github.com/huggingface/ml-intern

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = 'narcolepticchicken/patch-reward-model-v2'
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

For non-causal architectures, replace AutoModelForCausalLM with the appropriate AutoModel class.