token-classification-llmlingua2-phobert-bctn-323_sample-5_epoch_16k_fpt_v1

This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6698

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: 1e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.99	16	0.6736
No log	1.98	32	0.6717
No log	2.98	48	0.6711
No log	3.97	64	0.6702
No log	4.96	80	0.6698

Framework versions

• Transformers 4.39.0.dev0
• Pytorch 2.2.1+cu118
• Datasets 2.18.0
• Tokenizers 0.15.2