metadata
library_name: transformers
license: mit
base_model: jhu-clsp/mmBERT-base
tags:
- multi_label_classification
- generated_from_trainer
model-index:
- name: finetuned_model_emotion_detection
results: []
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: 0.3474
- F1 Macro: 0.5055
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_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro |
|---|---|---|---|---|
| No log | 1.0 | 223 | 0.2843 | 0.4052 |
| No log | 2.0 | 446 | 0.2643 | 0.4646 |
| 0.2521 | 3.0 | 669 | 0.3474 | 0.5055 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.2.0
- Tokenizers 0.22.1