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angelaupc/
reward_model

Name: reward_model
Availability: InStock

peft

safetensors

generated_from_trainer

meta-llama/Meta-Llama-3-8B-Instruct

adapter

llama3

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reward_model

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7036
Accuracy: 0.5236

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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.02
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7293	0.08	128	0.7252	0.4850
0.7412	0.15	256	0.6925	0.5386
0.7182	0.23	384	0.6954	0.5327
0.6997	0.3	512	0.6941	0.5277
0.7547	0.38	640	0.6959	0.5279
0.7123	0.45	768	0.6993	0.5252
0.7281	0.53	896	0.6962	0.5275
0.7169	0.6	1024	0.6986	0.5156
0.7244	0.68	1152	0.6981	0.5125
0.7199	0.75	1280	0.7000	0.5060
0.7311	0.83	1408	0.6959	0.5140
0.7123	0.9	1536	0.6956	0.5154
0.7344	0.98	1664	0.6970	0.5100
0.7105	1.05	1792	0.6933	0.5219
0.6947	1.13	1920	0.6944	0.5259
0.7261	1.21	2048	0.6960	0.5256
0.6997	1.28	2176	0.6974	0.5188
0.7442	1.36	2304	0.6960	0.5163
0.7004	1.43	2432	0.6987	0.5286
0.7089	1.51	2560	0.6982	0.5288
0.7142	1.58	2688	0.7014	0.5154
0.7364	1.66	2816	0.6997	0.5202
0.6915	1.73	2944	0.7043	0.5200
0.7322	1.81	3072	0.7037	0.5229
0.7524	1.88	3200	0.7019	0.5219
0.7192	1.96	3328	0.7036	0.5236

Framework versions

PEFT 0.12.0
Transformers 4.36.0
Pytorch 2.2.0
Datasets 2.20.0
Tokenizers 0.15.2

angelaupc/reward_model

reward_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

angelaupc/
reward_model