metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results: []
distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3068
- Accuracy: 0.9085
- F1 Score: 0.9086
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| 0.9641 | 1.0 | 250 | 0.6194 | 0.792 | 0.7819 |
| 0.4398 | 2.0 | 500 | 0.3389 | 0.883 | 0.8825 |
| 0.258 | 3.0 | 750 | 0.2948 | 0.8945 | 0.8951 |
| 0.1744 | 4.0 | 1000 | 0.2841 | 0.9035 | 0.9038 |
| 0.132 | 5.0 | 1250 | 0.2937 | 0.8985 | 0.8983 |
| 0.1078 | 6.0 | 1500 | 0.2770 | 0.9055 | 0.9054 |
| 0.0888 | 7.0 | 1750 | 0.3017 | 0.903 | 0.9028 |
| 0.0739 | 8.0 | 2000 | 0.2829 | 0.9095 | 0.9096 |
| 0.0611 | 9.0 | 2250 | 0.3062 | 0.91 | 0.9102 |
| 0.0506 | 10.0 | 2500 | 0.3068 | 0.9085 | 0.9086 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1