Model save
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README.md
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---
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library_name: transformers
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base_model: Hartunka/bert_base_km_5_v2
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: bert_base_km_5_v2_wnli
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bert_base_km_5_v2_wnli
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This model is a fine-tuned version of [Hartunka/bert_base_km_5_v2](https://huggingface.co/Hartunka/bert_base_km_5_v2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9396
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- Accuracy: 0.1549
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 256
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- eval_batch_size: 256
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- seed: 10
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 50
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.7687 | 1.0 | 3 | 0.7557 | 0.2676 |
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| 0.7017 | 2.0 | 6 | 0.7759 | 0.2113 |
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| 0.6899 | 3.0 | 9 | 0.7978 | 0.1690 |
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| 0.6828 | 4.0 | 12 | 0.8442 | 0.1549 |
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| 0.6741 | 5.0 | 15 | 0.8997 | 0.1549 |
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| 0.6788 | 6.0 | 18 | 0.9396 | 0.1549 |
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### Framework versions
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- Transformers 4.50.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.21.1
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logs/events.out.tfevents.1745274950.s_005_m.2836894.14
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 8477
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