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--- |
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license: apache-2.0 |
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base_model: 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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- f1 |
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model-index: |
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- name: Albert-finetuned-stationary-update |
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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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# Albert-finetuned-stationary-update |
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7542 |
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- Accuracy: 0.5967 |
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- F1: 0.5862 |
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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: 64 |
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- eval_batch_size: 64 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.3976 | 1.0 | 38 | 0.8830 | 0.6033 | 0.5849 | |
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| 0.3105 | 2.0 | 76 | 0.9030 | 0.63 | 0.5876 | |
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| 0.2256 | 3.0 | 114 | 1.2156 | 0.6333 | 0.6366 | |
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| 0.1788 | 4.0 | 152 | 1.3055 | 0.6 | 0.5857 | |
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| 0.161 | 5.0 | 190 | 1.2205 | 0.59 | 0.5808 | |
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| 0.1304 | 6.0 | 228 | 1.5496 | 0.5933 | 0.5804 | |
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| 0.1046 | 7.0 | 266 | 1.6266 | 0.59 | 0.5915 | |
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| 0.0966 | 8.0 | 304 | 1.6807 | 0.6033 | 0.5971 | |
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| 0.0649 | 9.0 | 342 | 1.7279 | 0.5967 | 0.5831 | |
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| 0.0697 | 10.0 | 380 | 1.7542 | 0.5967 | 0.5862 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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