JT000
/

LCIA_Test1

Text Classification

Generated from Trainer

Model card Files Files and versions

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Log in or Sign Up to review the conditions and access this model content.

LCIA_Test1

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

Loss: 2.0876

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: 2e-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
lr_scheduler_warmup_steps: 500
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	4	2.0903
No log	2.0	8	2.0892
No log	3.0	12	2.0876

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Tokenizers 0.19.1

Downloads last month: 2

Safetensors

Model size

0.1B params

Tensor type

F32

·

Model tree for JT000/LCIA_Test1

Base model

google-bert/bert-base-uncased

Finetuned

(6265)

this model

Evaluation results