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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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model-index: |
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- name: ALBERT_trainer_irony |
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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_trainer_irony |
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the irony dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6538 |
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- Accuracy: 0.6327 |
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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: 20 |
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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: 7 |
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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 | 144 | 0.7213 | 0.4901 | |
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| No log | 2.0 | 288 | 0.6935 | 0.5644 | |
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| No log | 3.0 | 432 | 0.6834 | 0.5906 | |
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| 0.6892 | 4.0 | 576 | 0.6651 | 0.6031 | |
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| 0.6892 | 5.0 | 720 | 0.6731 | 0.6063 | |
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| 0.6892 | 6.0 | 864 | 0.6892 | 0.5958 | |
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| 0.6185 | 7.0 | 1008 | 0.6750 | 0.6188 | |
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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 2.18.0 |
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- Tokenizers 0.15.2 |
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