eurobert210m_Sentiment_v2

This model is a fine-tuned version of EuroBERT/EuroBERT-210m on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0163
• Accuracy: 0.9964
• F1: 0.9964

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: 32
• eval_batch_size: 32
• 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: 100
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.3156	1.0	407	0.1217	0.9585	0.9586
0.1475	2.0	814	0.0722	0.9774	0.9775
0.0939	3.0	1221	0.0426	0.9869	0.9870
0.0739	4.0	1628	0.0341	0.9899	0.9899
0.0592	5.0	2035	0.0280	0.9912	0.9912
0.0389	6.0	2442	0.0225	0.9936	0.9936
0.0333	7.0	2849	0.0141	0.9955	0.9955
0.0335	8.0	3256	0.0322	0.9930	0.9930
0.0257	9.0	3663	0.0139	0.9957	0.9957
0.0219	10.0	4070	0.0098	0.9969	0.9969
0.0192	11.0	4477	0.0127	0.9959	0.9959
0.0253	12.0	4884	0.0284	0.9926	0.9926
0.0211	13.0	5291	0.0163	0.9964	0.9964

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.4.1
• Tokenizers 0.21.1