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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
model-index:
  - name: finetuned-Sentiment-classfication-DistilBert-model
    results: []

finetuned-Sentiment-classfication-DistilBert-model

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

  • Loss: 0.2764
  • Rmse: 0.2925

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 16

Training results

Training Loss Epoch Step Validation Loss Rmse
0.7292 2.72 500 0.3805 0.5119
0.1778 5.43 1000 0.2802 0.3530
0.0487 8.15 1500 0.2764 0.2925
0.0209 10.86 2000 0.2921 0.2860
0.0113 13.58 2500 0.3244 0.2884

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3