metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ellis-v3-emotion-leadership-multi-label
results: []
ellis-v3-emotion-leadership-multi-label
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1095
- Accuracy: 0.9728
- F1: 0.9318
- Precision: 0.9346
- Recall: 0.9289
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: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1396 | 1.0 | 5910 | 0.1235 | 0.9669 | 0.9169 | 0.9211 | 0.9127 |
| 0.1025 | 2.0 | 11820 | 0.1095 | 0.9728 | 0.9318 | 0.9346 | 0.9289 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1