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bert-distilled-multi_teacher_avg_logit_twitter_sentiment_07_alpha0.8
This model is a fine-tuned version of ArafatBHossain/distilbert-base-uncased-twitter_eval_sentiment_data on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3250
- Accuracy: 0.671
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4044 | 1.0 | 1875 | 0.3820 | 0.6655 |
0.2636 | 2.0 | 3750 | 0.3914 | 0.668 |
0.206 | 3.0 | 5625 | 0.3595 | 0.6655 |
0.1694 | 4.0 | 7500 | 0.3548 | 0.6725 |
0.1437 | 5.0 | 9375 | 0.3360 | 0.6725 |
0.1272 | 6.0 | 11250 | 0.3259 | 0.6755 |
0.1167 | 7.0 | 13125 | 0.3250 | 0.671 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1