21iridescent
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update model card README.md
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README.md
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license: cc-by-nc-sa-4.0
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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model-index:
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- name: output
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results: []
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# output
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This model is a fine-tuned version of [Babelscape/rebel-large](https://huggingface.co/Babelscape/rebel-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3052
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- Precision: 0.9444
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- Recall: 0.9444
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- F1-measure: 0.9444
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## Model description
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- total_train_batch_size: 32
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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:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-measure |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:----------:|
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| No log | 1.0 |
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| No log | 2.0 | 420 | 0.3027 | 0.9444 | 0.9444 | 0.9444 |
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| 0.3652 | 3.0 | 630 | 0.3052 | 0.9444 | 0.9444 | 0.9444 |
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### Framework versions
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license: cc-by-nc-sa-4.0
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tags:
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- generated_from_trainer
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model-index:
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- name: output
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results: []
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# output
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This model is a fine-tuned version of [Babelscape/rebel-large](https://huggingface.co/Babelscape/rebel-large) on an unknown dataset.
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## Model description
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- total_train_batch_size: 32
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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: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-measure |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:----------:|
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| No log | 1.0 | 236 | 0.3225 | 0.8889 | 0.8889 | 0.8889 |
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### Framework versions
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