BERT-FINETUNE-MBTI-LM-BERT-FINETUNE-MBTI-LM-JointBERT-Warmup-from-LM
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.7966
- Cls loss: 1.4255
- Lm loss: 4.4398
- Cls Accuracy: 0.6380
- Cls F1: 0.6319
- Cls Precision: 0.6416
- Cls Recall: 0.6380
- Perplexity: 84.76
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 |
---|---|---|---|---|---|---|---|---|---|---|
5.3087 | 1.0 | 3470 | 4.9005 | 1.4109 | 4.5474 | 0.6075 | 0.5981 | 0.6132 | 0.6075 | 94.39 |
4.8274 | 2.0 | 6940 | 4.7987 | 1.3448 | 4.4621 | 0.6242 | 0.6193 | 0.6381 | 0.6242 | 86.67 |
4.6472 | 3.0 | 10410 | 4.7966 | 1.4255 | 4.4398 | 0.6380 | 0.6319 | 0.6416 | 0.6380 | 84.76 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
- Downloads last month
- 26
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.