finetuned-multilingual-sentiment-analysis

This model is a fine-tuned version of tabularisai/multilingual-sentiment-analysis on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.1996
• Accuracy: 0.4938

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: 9
• eval_batch_size: 9
• 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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.2653	1.0	1167	1.2070	0.4787
1.0571	2.0	2334	1.1996	0.4938
0.8886	3.0	3501	1.2983	0.4871

Framework versions

• Transformers 4.51.3
• Pytorch 2.7.0+cpu
• Datasets 3.6.0
• Tokenizers 0.21.1