imdb / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased-finetuned-sst-2-english
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: imdb
    results: []

imdb

This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2032
  • Accuracy: 0.927
  • Precision: 0.9241
  • Recall: 0.9318
  • F1: 0.9280

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-06
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.2612 1.0 625 0.2290 0.9122 0.9080 0.9191 0.9135
0.218 2.0 1250 0.2174 0.919 0.9114 0.9298 0.9205
0.2019 3.0 1875 0.2120 0.922 0.9197 0.9263 0.9230
0.1806 4.0 2500 0.2070 0.9214 0.9122 0.9342 0.9230
0.1711 5.0 3125 0.2052 0.9244 0.9191 0.9322 0.9256
0.1605 6.0 3750 0.2032 0.9236 0.9164 0.9338 0.9250
0.1639 7.0 4375 0.2062 0.9244 0.9152 0.9370 0.9260
0.1544 8.0 5000 0.2026 0.9268 0.9265 0.9287 0.9276
0.148 9.0 5625 0.2035 0.9274 0.9212 0.9362 0.9286
0.144 10.0 6250 0.2032 0.927 0.9241 0.9318 0.9280

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1