amazon_topical_chat_sentiment
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: 1.1237
- Accuracy: 0.5687
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.199 | 1.0 | 9419 | 1.1807 | 0.5348 |
1.1383 | 2.0 | 18838 | 1.1487 | 0.5457 |
1.1036 | 3.0 | 28257 | 1.1368 | 0.5558 |
1.0971 | 4.0 | 37676 | 1.1226 | 0.5605 |
1.0679 | 5.0 | 47095 | 1.1223 | 0.5634 |
1.0528 | 6.0 | 56514 | 1.1156 | 0.5696 |
1.0245 | 7.0 | 65933 | 1.1158 | 0.5683 |
1.0279 | 8.0 | 75352 | 1.1140 | 0.5687 |
1.0152 | 9.0 | 84771 | 1.1127 | 0.5690 |
0.9794 | 10.0 | 94190 | 1.1179 | 0.5687 |
0.9717 | 11.0 | 103609 | 1.1200 | 0.5700 |
0.9654 | 12.0 | 113028 | 1.1223 | 0.5692 |
0.9703 | 13.0 | 122447 | 1.1232 | 0.5700 |
0.9545 | 14.0 | 131866 | 1.1237 | 0.5687 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
distilbert/distilbert-base-uncased