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--- |
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base_model: facebook/mbart-large-cc25 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: nl+no_processing |
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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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# nl+no_processing |
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This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co./facebook/mbart-large-cc25) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6038 |
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- Smatch Precision: 73.7 |
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- Smatch Recall: 76.48 |
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- Smatch Fscore: 75.06 |
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- Smatch Unparsable: 0 |
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- Percent Not Recoverable: 0.2323 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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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: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Smatch Precision | Smatch Recall | Smatch Fscore | Smatch Unparsable | Percent Not Recoverable | |
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|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:-------------:|:-----------------:|:-----------------------:| |
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| 0.8025 | 1.0 | 3477 | 1.3793 | 18.51 | 65.71 | 28.88 | 0 | 0.0 | |
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| 0.13 | 2.0 | 6954 | 0.9377 | 27.0 | 71.3 | 39.16 | 0 | 0.1161 | |
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| 0.0953 | 3.0 | 10431 | 0.7509 | 34.09 | 72.74 | 46.42 | 0 | 0.1161 | |
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| 0.1386 | 4.0 | 13908 | 0.8524 | 33.38 | 73.32 | 45.87 | 2 | 0.0 | |
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| 0.0974 | 5.0 | 17385 | 0.6957 | 41.69 | 73.92 | 53.31 | 0 | 0.0 | |
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| 0.0705 | 6.0 | 20862 | 0.6145 | 47.98 | 75.12 | 58.55 | 0 | 0.0 | |
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| 0.2265 | 7.0 | 24339 | 0.6439 | 47.06 | 75.53 | 57.99 | 0 | 0.0 | |
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| 0.0506 | 8.0 | 27817 | 0.5974 | 53.0 | 76.95 | 62.77 | 0 | 0.0 | |
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| 0.064 | 9.0 | 31294 | 0.6387 | 51.83 | 77.47 | 62.11 | 0 | 0.0 | |
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| 0.0112 | 10.0 | 34771 | 0.6066 | 54.82 | 76.98 | 64.03 | 0 | 0.0 | |
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| 0.047 | 11.0 | 38248 | 0.5970 | 60.36 | 77.04 | 67.69 | 0 | 0.0 | |
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| 0.0134 | 12.0 | 41725 | 0.5675 | 61.72 | 77.15 | 68.58 | 0 | 0.0 | |
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| 0.0656 | 13.0 | 45202 | 0.6210 | 62.8 | 76.92 | 69.15 | 0 | 0.0581 | |
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| 0.015 | 14.0 | 48679 | 0.6257 | 62.8 | 77.32 | 69.31 | 0 | 0.0 | |
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| 0.0134 | 15.0 | 52156 | 0.5635 | 66.7 | 77.34 | 71.63 | 0 | 0.1161 | |
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| 0.0265 | 16.0 | 55634 | 0.5839 | 67.61 | 76.76 | 71.89 | 0 | 0.0581 | |
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| 0.0219 | 17.0 | 59111 | 0.5894 | 68.66 | 77.43 | 72.78 | 0 | 0.1161 | |
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| 0.0008 | 18.0 | 62588 | 0.5981 | 68.44 | 77.57 | 72.72 | 0 | 0.0 | |
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| 0.0157 | 19.0 | 66065 | 0.6184 | 69.88 | 77.42 | 73.46 | 0 | 0.0581 | |
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| 0.0334 | 20.0 | 69542 | 0.6026 | 70.76 | 77.37 | 73.92 | 0 | 0.2323 | |
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| 0.0619 | 21.0 | 73019 | 0.6021 | 72.03 | 77.0 | 74.44 | 0 | 0.1742 | |
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| 0.0075 | 22.0 | 76496 | 0.6166 | 72.33 | 76.74 | 74.47 | 0 | 0.0581 | |
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| 0.0164 | 23.0 | 79973 | 0.6100 | 72.75 | 77.03 | 74.83 | 0 | 0.2323 | |
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| 0.0011 | 24.0 | 83451 | 0.6037 | 73.7 | 76.51 | 75.08 | 0 | 0.2323 | |
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| 0.0865 | 25.0 | 86925 | 0.6038 | 73.7 | 76.48 | 75.06 | 0 | 0.2323 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.2 |
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- Tokenizers 0.13.3 |
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