finetuned_model_emotion_detection_es

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

• Loss: 0.6032
• F1 Macro: 0.8405

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: 6
• eval_batch_size: 6
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro
0.4917	1.0	2134	0.4718	0.8308
0.3216	2.0	4268	0.4989	0.8271
0.1734	3.0	6402	0.6032	0.8405

Framework versions

• Transformers 5.4.0
• Pytorch 2.10.0+cu128
• Datasets 4.8.4
• Tokenizers 0.22.2