distilbert-base-uncased-finetuned-emotion_new
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: 0.8847
- Accuracy: 0.8
- F1: 0.7333
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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5408 | 1.0 | 4 | 0.7674 | 0.8 | 0.7333 |
| 0.4368 | 2.0 | 8 | 0.7471 | 0.8 | 0.7333 |
| 0.3222 | 3.0 | 12 | 0.7318 | 0.8 | 0.7333 |
| 0.4061 | 4.0 | 16 | 0.7289 | 0.8 | 0.7333 |
| 0.3774 | 5.0 | 20 | 0.7732 | 0.8 | 0.7333 |
| 0.3304 | 6.0 | 24 | 0.7874 | 0.8 | 0.7333 |
| 0.3042 | 7.0 | 28 | 0.8036 | 0.8 | 0.7333 |
| 0.4571 | 8.0 | 32 | 0.8038 | 0.8 | 0.7333 |
| 0.1992 | 9.0 | 36 | 0.8271 | 0.8 | 0.7333 |
| 0.2661 | 10.0 | 40 | 0.8498 | 0.8 | 0.7333 |
| 0.2361 | 11.0 | 44 | 0.8582 | 0.8 | 0.7333 |
| 0.2292 | 12.0 | 48 | 0.8620 | 0.8 | 0.7333 |
| 0.2363 | 13.0 | 52 | 0.8678 | 0.8 | 0.7333 |
| 0.2574 | 14.0 | 56 | 0.8672 | 0.8 | 0.7333 |
| 0.5177 | 15.0 | 60 | 0.8668 | 0.8 | 0.7333 |
| 0.226 | 16.0 | 64 | 0.8726 | 0.8 | 0.7333 |
| 0.1726 | 17.0 | 68 | 0.8788 | 0.8 | 0.7333 |
| 0.2439 | 18.0 | 72 | 0.8823 | 0.8 | 0.7333 |
| 0.2005 | 19.0 | 76 | 0.8842 | 0.8 | 0.7333 |
| 0.2541 | 20.0 | 80 | 0.8847 | 0.8 | 0.7333 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.2