trained_dilibert_sentiment_analysis

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

• Loss: 0.3948
• Accuracy: 0.906
• Confusion Matrix: [[174, 46], [48, 732]]

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: 1e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Confusion Matrix
No log	1.0	188	0.2507	0.905	[[168, 52], [43, 737]]
No log	2.0	376	0.2797	0.904	[[172, 48], [48, 732]]
0.2241	3.0	564	0.3635	0.906	[[154, 66], [28, 752]]
0.2241	4.0	752	0.3798	0.908	[[171, 49], [43, 737]]
0.2241	5.0	940	0.3948	0.906	[[174, 46], [48, 732]]

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1