clasificador2-muchocine

This model is a fine-tuned version of GKLMIP/bert-khmer-base-uncased-tokenized on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.5195
• Accuracy: 0.3313

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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	339	1.5292	0.3313
1.5525	2.0	678	1.5392	0.2057
1.5301	3.0	1017	1.5195	0.3313

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0