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Angelectronic/
llama3-ViMMRC-Answer

Name: llama3-ViMMRC-Answer
Availability: InStock

generated_from_trainer

unsloth/llama-3-8b-Instruct-bnb-4bit

adapter

apache-2.0

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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

Angelectronic/llama3-ViMMRC-Answer