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bert-base-uncased-bert-base-uncased-mc-weight1-epoch15
GItaf/bert-base-uncased-bert-base-uncased-mc-weight1-epoch15
bert-base-uncased-bert-base-uncased-mc-weight1-epoch15 is a text generation model from GItaf. Use it when you need the model to write or continue text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Generation
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Oct 2, 2022
- Updated
- Oct 4, 2022
- SHA
- 71d98a61
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
bert-base-uncased-bert-base-uncased-mc-weight1-epoch15
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 7.8027
- Cls loss: 3.4449
- Lm loss: 4.3556
- Cls Accuracy: 0.5706
- Cls F1: 0.5697
- Cls Precision: 0.5753
- Cls Recall: 0.5706
- Perplexity: 77.91
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
|---|---|---|---|---|---|---|---|---|---|---|
| 6.9526 | 1.0 | 3470 | 6.3154 | 1.7748 | 4.5399 | 0.4991 | 0.4577 | 0.4421 | 0.4991 | 93.68 |
| 6.0876 | 2.0 | 6940 | 6.1427 | 1.6773 | 4.4643 | 0.5545 | 0.5342 | 0.5717 | 0.5545 | 86.86 |
| 5.7231 | 3.0 | 10410 | 6.0206 | 1.5955 | 4.4240 | 0.5902 | 0.5759 | 0.6020 | 0.5902 | 83.43 |
| 5.3877 | 4.0 | 13880 | 5.9857 | 1.5772 | 4.4073 | 0.6092 | 0.6031 | 0.6052 | 0.6092 | 82.05 |
| 5.1092 | 5.0 | 17350 | 6.3742 | 1.9981 | 4.3748 | 0.5942 | 0.5901 | 0.5964 | 0.5942 | 79.42 |
| 4.8504 | 6.0 | 20820 | 6.4511 | 2.0776 | 4.3737 | 0.5890 | 0.5875 | 0.6041 | 0.5890 | 79.34 |
| 4.6369 | 7.0 | 24290 | 6.9857 | 2.6268 | 4.3571 | 0.5827 | 0.5796 | 0.5979 | 0.5827 | 78.03 |
| 4.4667 | 8.0 | 27760 | 6.9550 | 2.6075 | 4.3458 | 0.5833 | 0.5831 | 0.5904 | 0.5833 | 77.16 |
| 4.3127 | 9.0 | 31230 | 7.2041 | 2.8518 | 4.3504 | 0.5902 | 0.5856 | 0.5935 | 0.5902 | 77.51 |
| 4.1777 | 10.0 | 34700 | 7.4233 | 3.0746 | 4.3467 | 0.5793 | 0.5770 | 0.5829 | 0.5793 | 77.22 |
| 4.0871 | 11.0 | 38170 | 7.4997 | 3.1488 | 4.3489 | 0.5746 | 0.5749 | 0.5853 | 0.5746 | 77.39 |
| 3.9991 | 12.0 | 41640 | 7.6636 | 3.3113 | 4.3502 | 0.5602 | 0.5605 | 0.5676 | 0.5602 | 77.49 |
| 3.9461 | 13.0 | 45110 | 7.6065 | 3.2514 | 4.3530 | 0.5695 | 0.5690 | 0.5738 | 0.5695 | 77.71 |
| 3.9013 | 14.0 | 48580 | 7.7562 | 3.4017 | 4.3523 | 0.5787 | 0.5785 | 0.5823 | 0.5787 | 77.65 |
| 3.8731 | 15.0 | 52050 | 7.8027 | 3.4449 | 4.3556 | 0.5706 | 0.5697 | 0.5753 | 0.5706 | 77.91 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Generation
- Library
- transformers
- Type
- bert
- Created
- Oct 2, 2022
- Updated
- Oct 4, 2022