metadata

license: apache-2.0
tags:
  - generated_from_trainer
base_model: bert-base-cased
model-index:
  - name: finetuned-Sentiment-classfication-BERT-model
    results: []

finetuned-Sentiment-classfication-BERT-model

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

Loss: 0.6056
Rmse: 0.6890

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: 3e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rmse
0.7754	2.0	500	0.6056	0.6890
0.3975	4.0	1000	0.6982	0.6452
0.1308	6.0	1500	1.0715	0.6643
0.0526	8.0	2000	1.3439	0.6571
0.0241	10.0	2500	1.4676	0.6695

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3