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--- |
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license: apache-2.0 |
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tags: |
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- classification |
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- generated_from_trainer |
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datasets: |
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- poem_sentiment |
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metrics: |
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- accuracy |
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base_model: bert-base-uncased |
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model-index: |
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- name: clasificador-poem-sentiment |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: poem_sentiment |
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type: poem_sentiment |
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config: default |
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split: train |
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args: default |
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metrics: |
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- type: accuracy |
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value: 0.9038461538461539 |
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name: Accuracy |
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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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# clasificador-poem-sentiment |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the poem_sentiment dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5088 |
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- Accuracy: 0.9038 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 3.0 |
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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 | 112 | 0.4324 | 0.8654 | |
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| No log | 2.0 | 224 | 0.4070 | 0.875 | |
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| No log | 3.0 | 336 | 0.5088 | 0.9038 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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