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README.md
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---
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library_name: transformers
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base_model: Hartunka/tiny_bert_km_100_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: tiny_bert_km_100_v2_rte
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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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# tiny_bert_km_100_v2_rte
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This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v2](https://huggingface.co/Hartunka/tiny_bert_km_100_v2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7470
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- Accuracy: 0.5307
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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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| 0.6985 | 1.0 | 10 | 0.6881 | 0.5379 |
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| 0.6784 | 2.0 | 20 | 0.6940 | 0.5487 |
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| 0.6618 | 3.0 | 30 | 0.6917 | 0.5776 |
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| 0.6379 | 4.0 | 40 | 0.6999 | 0.5451 |
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| 0.6094 | 5.0 | 50 | 0.7121 | 0.5487 |
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| 0.5673 | 6.0 | 60 | 0.7470 | 0.5307 |
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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.1745290334.s_005_m.2836625.80
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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 8480
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