EMOTION-AI
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4780
- Accuracy: 0.5616
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9982 | 271 | 1.5711 | 0.5464 |
| 1.5442 | 2.0 | 543 | 1.4952 | 0.5638 |
| 1.5442 | 2.9982 | 814 | 1.4755 | 0.5657 |
| 1.3192 | 3.9926 | 1084 | 1.4780 | 0.5616 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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Model tree for Hemg/EMOTION-AI
Base model
distilbert/distilbert-base-uncased