reward_model – AI Model by lillybak | AlphaNeural AI

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lillybak/
reward_model

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text-classification

generated_from_trainer

distilbert/distilroberta-base

autotrain_compatible

endpoints_compatible

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reward_model

This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7183
Accuracy: 0.45

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: 5e-05
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.01	50	0.6941	0.49
No log	0.02	100	0.7068	0.44
No log	0.03	150	0.6991	0.47
No log	0.04	200	0.6954	0.5
No log	0.05	250	0.6957	0.55
No log	0.06	300	0.6958	0.5
No log	0.07	350	0.7203	0.45
No log	0.08	400	0.7129	0.47
No log	0.09	450	0.7197	0.45
0.6877	0.1	500	0.7183	0.45

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1