distilbert-base-uncased-sentiment_analysis_model

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Accuracy: 0.904
• Loss: 0.2909

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: 0.001
• train_batch_size: 96
• eval_batch_size: 96
• seed: 42
• optimizer: Use OptimizerNames.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: 10

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
No log	1.0	11	0.799	0.5024
No log	2.0	22	0.891	0.2789
No log	3.0	33	0.886	0.2708
No log	4.0	44	0.903	0.2456
No log	5.0	55	0.897	0.2568
No log	6.0	66	0.904	0.2667
No log	7.0	77	0.907	0.2691
No log	8.0	88	0.899	0.2836
No log	9.0	99	0.907	0.2894
No log	10.0	110	0.904	0.2909

Framework versions

• PEFT 0.14.0
• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.4.0
• Tokenizers 0.21.0