llama3-ViMMRC-Answer

This model is a fine-tuned version of unsloth/llama-3-8b-Instruct-bnb-4bit on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1419
• Accuracy: 0.885662

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

ViMMRC train and test set

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 16
• eval_batch_size: 8
• seed: 3407
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 5
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
3.2677	0.3306	10	0.1883
0.4922	0.6612	20	0.2020
0.4551	0.9917	30	0.1609
0.4292	1.3223	40	0.2353
0.4361	1.6529	50	0.1758
0.4323	1.9835	60	0.1515
0.4232	2.3140	70	0.1451
0.411	2.6446	80	0.1424
0.413	2.9752	90	0.1419

Framework versions

• PEFT 0.10.0
• Transformers 4.40.2
• Pytorch 2.3.0
• Datasets 2.19.1
• Tokenizers 0.19.1