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bert_base_km_100_v2
Hartunka/bert_base_km_100_v2
bert_base_km_100_v2 is a machine learning model from Hartunka. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Apr 15, 2025
- Updated
- Apr 20, 2025
- SHA
- def1f9d5
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_km_100_v2
This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-km-100_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 7.0530
- Accuracy: 0.1534
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: 0.0001
- train_batch_size: 96
- eval_batch_size: 96
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 7.0906 | 4.1982 | 10000 | 7.2316 | 0.1493 |
| 6.5625 | 8.3963 | 20000 | 7.0367 | 0.1526 |
| 6.2634 | 12.5945 | 30000 | 7.2296 | 0.1545 |
| 6.0994 | 16.7926 | 40000 | 7.4918 | 0.1523 |
| 6.0062 | 20.9908 | 50000 | 7.3908 | 0.1511 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
- Library
- transformers
- Type
- distilbert
- Created
- Apr 15, 2025
- Updated
- Apr 20, 2025