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finetuned_model_emotion_detection – AI Model by Carmendlr | AlphaNeural AI
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finetuned_model_emotion_detection
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transformers
safetensors
modernbert
text-classification
multi_label_classification
generated_from_trainer
jhu-clsp/mmBERT-base
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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finetuned_model_emotion_detection
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: 0.3600
F1 Macro: 0.5039
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: 16
eval_batch_size: 16
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
0.2714
1.0
223
0.2673
0.4397
0.1729
2.0
446
0.2642
0.4684
0.0734
3.0
669
0.3600
0.5039
Framework versions
Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 4.7.0
Tokenizers 0.22.2
