metadata
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: bge-m3_emotion_ft_0416
results: []
bge-m3_emotion_ft_0416
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1023
- Accuracy: 0.944
- F1: 0.9442
- Precision: 0.9176
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use 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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision |
|---|---|---|---|---|---|---|
| 0.4266 | 1.0 | 250 | 0.2097 | 0.929 | 0.9294 | 0.8987 |
| 0.1352 | 2.0 | 500 | 0.1182 | 0.941 | 0.9406 | 0.9212 |
| 0.0965 | 3.0 | 750 | 0.1046 | 0.949 | 0.9493 | 0.9185 |
| 0.0753 | 4.0 | 1000 | 0.1023 | 0.944 | 0.9442 | 0.9176 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3