End of training
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README.md
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---
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license: apache-2.0
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base_model: albert/albert-base-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: lenate_model_12_albert-base-v2
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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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# lenate_model_12_albert-base-v2
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This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5494
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- Accuracy: 0.7622
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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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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| No log | 1.0 | 355 | 0.6467 | 0.7212 |
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| 0.7746 | 2.0 | 710 | 0.5847 | 0.7241 |
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| 0.5448 | 3.0 | 1065 | 0.5494 | 0.7622 |
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| 0.5448 | 4.0 | 1420 | 0.6416 | 0.7368 |
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| 0.3705 | 5.0 | 1775 | 0.6439 | 0.7735 |
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| 0.2112 | 6.0 | 2130 | 0.8791 | 0.7643 |
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| 0.2112 | 7.0 | 2485 | 1.1350 | 0.7657 |
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| 0.1012 | 8.0 | 2840 | 1.3247 | 0.7721 |
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| 0.0294 | 9.0 | 3195 | 1.4469 | 0.7699 |
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| 0.0112 | 10.0 | 3550 | 1.4783 | 0.7699 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.0
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- Tokenizers 0.15.2
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