test_trainer

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

• Loss: 1.1535
• Accuracy: 0.846

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	63	0.4610	0.818
No log	2.0	126	0.6583	0.828
No log	3.0	189	0.6051	0.848
No log	4.0	252	0.9601	0.83
No log	5.0	315	0.8297	0.858
No log	6.0	378	0.9417	0.866
No log	7.0	441	0.9992	0.86
0.1794	8.0	504	1.1292	0.846
0.1794	9.0	567	1.1538	0.842
0.1794	10.0	630	1.1535	0.846

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1