metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-emotion-model-5-v2
results: []
finetuning-emotion-model-5-v2
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1559
- Accuracy: 0.5885
- F1: 0.5876
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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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 | F1 |
|---|---|---|---|---|---|
| 0.9413 | 1.0 | 2250 | 0.9176 | 0.5816 | 0.5680 |
| 0.8226 | 2.0 | 4500 | 0.8871 | 0.6051 | 0.6027 |
| 0.6739 | 3.0 | 6750 | 0.9854 | 0.5969 | 0.5971 |
| 0.4879 | 4.0 | 9000 | 1.1559 | 0.5885 | 0.5876 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1