eo_train1-10_eval11

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

• Loss: 0.6932
• Accuracy: 0.5

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: 0.001
• train_batch_size: 128
• eval_batch_size: 128
• seed: 7658372
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 3000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0	0	2.6863	0.0
0.6284	100.0	100	0.7859	0.5
0.548	200.0	200	0.7353	0.5
0.5022	300.0	300	0.6964	0.5
0.6935	400.0	400	0.6936	0.5
0.6933	500.0	500	0.6933	0.5
0.6932	600.0	600	0.6932	0.5
0.6932	700.0	700	0.6932	0.5
0.6932	800.0	800	0.6932	0.5
0.6932	900.0	900	0.6932	0.5
0.6932	1000.0	1000	0.6932	0.5
0.6932	1100.0	1100	0.6932	0.5
0.6932	1200.0	1200	0.6932	0.5
0.6932	1300.0	1300	0.6932	0.5
0.6932	1400.0	1400	0.6932	0.5
0.6932	1500.0	1500	0.6932	0.5
0.6932	1600.0	1600	0.6932	0.5
0.6932	1700.0	1700	0.6932	0.5
0.6932	1800.0	1800	0.6932	0.5
0.6932	1900.0	1900	0.6932	0.5
0.6932	2000.0	2000	0.6932	0.5
0.6932	2100.0	2100	0.6932	0.5
0.6932	2200.0	2200	0.6932	0.5
0.6932	2300.0	2300	0.6932	0.5
0.6932	2400.0	2400	0.6932	0.5
0.6932	2500.0	2500	0.6932	0.5
0.6932	2600.0	2600	0.6932	0.5
0.6932	2700.0	2700	0.6932	0.5
0.6932	2800.0	2800	0.6932	0.5
0.6932	2900.0	2900	0.6932	0.5
0.6932	3000.0	3000	0.6932	0.5

Framework versions

• Transformers 4.46.0
• Pytorch 2.5.1
• Datasets 3.1.0
• Tokenizers 0.20.1