BERT-FINETUNE-MBTI-CLS-BERT-FINETUNE-MBTI-CLS-JointBERT-Warmup-from-CLS
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.3549
- Cls loss: 2.1311
- Lm loss: 4.8216
- Cls Accuracy: 0.6058
- Cls F1: 0.6037
- Cls Precision: 0.6084
- Cls Recall: 0.6058
- Perplexity: 124.17
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
---|---|---|---|---|---|---|---|---|---|---|
5.778 | 1.0 | 3470 | 5.5656 | 1.9246 | 5.0840 | 0.5931 | 0.5907 | 0.5968 | 0.5931 | 161.43 |
5.1443 | 2.0 | 6940 | 5.3831 | 2.0178 | 4.8783 | 0.6069 | 0.6057 | 0.6177 | 0.6069 | 131.40 |
4.9386 | 3.0 | 10410 | 5.3549 | 2.1311 | 4.8216 | 0.6058 | 0.6037 | 0.6084 | 0.6058 | 124.17 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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