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: 0.3239
- F1 Macro: 0.5138
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 |
|---|---|---|---|---|
| No log | 1.0 | 223 | 0.2739 | 0.3879 |
| No log | 2.0 | 446 | 0.2645 | 0.4622 |
| 0.2603 | 3.0 | 669 | 0.3239 | 0.5138 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.2
- Tokenizers 0.22.2
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Model tree for canl0we/finetuned_model_emotion_detection
Base model
jhu-clsp/mmBERT-base