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--- |
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license: apache-2.0 |
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base_model: alex-miller/ODABert |
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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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- precision |
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- recall |
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model-index: |
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- name: multi-dimensional-disability |
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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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# multi-dimensional-disability |
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This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6084 |
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- Accuracy: 0.9116 |
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- F1: 0.8471 |
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- Precision: 0.8029 |
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- Recall: 0.8966 |
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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: 1e-06 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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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 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.9604 | 1.0 | 437 | 0.9473 | 0.8617 | 0.7483 | 0.7446 | 0.7519 | |
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| 0.8897 | 2.0 | 874 | 0.8169 | 0.8804 | 0.7995 | 0.7380 | 0.8721 | |
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| 0.8054 | 3.0 | 1311 | 0.7170 | 0.8858 | 0.8028 | 0.7601 | 0.8505 | |
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| 0.6757 | 4.0 | 1748 | 0.6679 | 0.8921 | 0.8164 | 0.7631 | 0.8777 | |
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| 0.6153 | 5.0 | 2185 | 0.6279 | 0.8992 | 0.8275 | 0.7772 | 0.8847 | |
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| 0.5782 | 6.0 | 2622 | 0.5773 | 0.8995 | 0.8305 | 0.7705 | 0.9008 | |
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| 0.5435 | 7.0 | 3059 | 0.6106 | 0.9072 | 0.8401 | 0.7937 | 0.8924 | |
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| 0.5333 | 8.0 | 3496 | 0.6141 | 0.9079 | 0.8435 | 0.7878 | 0.9078 | |
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| 0.5349 | 9.0 | 3933 | 0.6056 | 0.9097 | 0.8448 | 0.7964 | 0.8994 | |
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| 0.539 | 10.0 | 4370 | 0.6084 | 0.9116 | 0.8471 | 0.8029 | 0.8966 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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