rm1

This model is a fine-tuned version of EleutherAI/pythia-160m on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.5286
• Accuracy: 0.8456

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: 3e-06
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6883	0.0621	5	0.6846	0.7537
0.6723	0.1242	10	0.6717	0.7978
0.6761	0.1863	15	0.6559	0.8162
0.6627	0.2484	20	0.6379	0.8125
0.6156	0.3104	25	0.6175	0.8125
0.6232	0.3725	30	0.5937	0.8272
0.5985	0.4346	35	0.5711	0.8456
0.6024	0.4967	40	0.5549	0.8309
0.5906	0.5588	45	0.5449	0.8346
0.6184	0.6209	50	0.5383	0.8419
0.5379	0.6830	55	0.5338	0.8382
0.564	0.7451	60	0.5312	0.8456
0.5635	0.8071	65	0.5299	0.8456
0.5892	0.8692	70	0.5292	0.8493
0.5416	0.9313	75	0.5288	0.8456
0.5994	0.9934	80	0.5286	0.8456

Framework versions

• Transformers 4.40.1
• Pytorch 2.2.0+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1