metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: imdb-distilbert-sentiment
results: []
imdb-distilbert-sentiment
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: 0.4325
- Accuracy: 0.8796
- Precision: 0.8725
- Recall: 0.8892
- F1: 0.8808
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3175 | 1.0 | 1563 | 0.3278 | 0.8607 | 0.9120 | 0.7985 | 0.8515 |
| 0.2139 | 2.0 | 3126 | 0.3392 | 0.8773 | 0.8679 | 0.8901 | 0.8788 |
| 0.1325 | 3.0 | 4689 | 0.4325 | 0.8796 | 0.8725 | 0.8892 | 0.8808 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.5.1+cu121
- Datasets 4.1.1
- Tokenizers 0.22.1