metadata

license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: distilbert-base-uncased-IDMB-sentiment-analysis
    results: []

distilbert-base-uncased-IDMB-sentiment-analysis

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

Loss: 0.3468
F1: 0.7745
Accuracy: 0.9373

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.239	1.0	1250	0.1846	0.7436	0.928
0.1181	2.0	2500	0.2053	0.7473	0.9277
0.0573	3.0	3750	0.2772	0.7570	0.9327
0.0269	4.0	5000	0.3206	0.7706	0.9363
0.0127	5.0	6250	0.3468	0.7745	0.9373

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2