distilbert_dair-ai_emotion_20240730_e20_cos
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the dair-ai/emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1601
- Accuracy: 0.9395
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: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 32 | 1.2155 | 0.576 |
No log | 2.0 | 64 | 0.7162 | 0.7685 |
No log | 3.0 | 96 | 0.3572 | 0.9045 |
No log | 4.0 | 128 | 0.2206 | 0.9265 |
No log | 5.0 | 160 | 0.1939 | 0.926 |
No log | 6.0 | 192 | 0.1677 | 0.9335 |
No log | 7.0 | 224 | 0.1637 | 0.9345 |
No log | 8.0 | 256 | 0.1632 | 0.932 |
No log | 9.0 | 288 | 0.1522 | 0.9385 |
No log | 10.0 | 320 | 0.1505 | 0.937 |
No log | 11.0 | 352 | 0.1539 | 0.9375 |
No log | 12.0 | 384 | 0.1554 | 0.9375 |
No log | 13.0 | 416 | 0.1564 | 0.9395 |
No log | 14.0 | 448 | 0.1581 | 0.9405 |
No log | 15.0 | 480 | 0.1597 | 0.9405 |
0.2897 | 16.0 | 512 | 0.1590 | 0.94 |
0.2897 | 17.0 | 544 | 0.1585 | 0.94 |
0.2897 | 18.0 | 576 | 0.1604 | 0.9385 |
0.2897 | 19.0 | 608 | 0.1602 | 0.9395 |
0.2897 | 20.0 | 640 | 0.1601 | 0.9395 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Chahnwoo/distilbert_dair-ai_emotion_20240730_e20_cos
Base model
distilbert/distilbert-base-uncased