metadata
library_name: transformers
license: apache-2.0
base_model: sauc-abadal-lloret/distilbert-base-uncased-ft-imdb-mlm
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-ft-imdb-mlm-ft-imdb-sentiment-classifier
results: []
distilbert-base-uncased-ft-imdb-mlm-ft-imdb-sentiment-classifier
This model is a fine-tuned version of sauc-abadal-lloret/distilbert-base-uncased-ft-imdb-mlm on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2862
- Precision: 0.9244
- Recall: 0.9016
- F1: 0.9129
- Accuracy: 0.916
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2988 | 1.0 | 313 | 0.2395 | 0.8938 | 0.9139 | 0.9037 | 0.905 |
| 0.1755 | 2.0 | 626 | 0.2566 | 0.9121 | 0.8934 | 0.9027 | 0.906 |
| 0.1105 | 3.0 | 939 | 0.2862 | 0.9244 | 0.9016 | 0.9129 | 0.916 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1