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--- |
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base_model: facebook/mbart-large-cc25 |
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language: |
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- nl |
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- es |
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--- |
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# ES and NL to AMR parsing (stratified) |
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This version was trained on a subselection of the data. The AMR 3.0 corpus was translated to all the relevant languages. We then divided the dataset so |
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that in total we only see half of each language's dataset (so that in total we only see the full AMR 3.0 corpus in size once). In other words, |
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all languages were undersampled for research purposes. |
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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: 0.6212 |
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- Smatch Precision: 72.94 |
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- Smatch Recall: 75.83 |
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- Smatch Fscore: 74.36 |
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- Smatch Unparsable: 0 |
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- Percent Not Recoverable: 0.4065 |
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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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| 0.4098 | 1.0 | 3477 | 1.3168 | 17.61 | 63.89 | 27.62 | 0 | 0.0 | |
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| 0.3307 | 2.0 | 6954 | 1.0109 | 21.08 | 68.69 | 32.26 | 0 | 0.0581 | |
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| 0.1253 | 3.0 | 10431 | 0.9193 | 32.88 | 71.46 | 45.04 | 0 | 0.0 | |
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| 0.1665 | 4.0 | 13908 | 0.7549 | 35.07 | 72.54 | 47.29 | 0 | 0.0 | |
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| 0.0435 | 5.0 | 17385 | 0.8298 | 40.25 | 74.91 | 52.37 | 0 | 0.0581 | |
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| 0.2156 | 6.0 | 20862 | 0.6525 | 45.7 | 75.11 | 56.82 | 0 | 0.0 | |
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| 0.133 | 7.0 | 24339 | 0.6548 | 47.7 | 75.36 | 58.42 | 0 | 0.0 | |
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| 0.0624 | 8.0 | 27817 | 0.6054 | 53.59 | 75.18 | 62.57 | 0 | 0.0 | |
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| 0.0841 | 9.0 | 31294 | 0.6496 | 54.68 | 75.01 | 63.25 | 0 | 0.0581 | |
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| 0.1073 | 10.0 | 34771 | 0.5960 | 55.76 | 76.35 | 64.45 | 0 | 0.0 | |
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| 0.048 | 11.0 | 38248 | 0.5924 | 60.99 | 76.4 | 67.83 | 0 | 0.0 | |
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| 0.0341 | 12.0 | 41725 | 0.5880 | 60.39 | 76.31 | 67.42 | 0 | 0.0581 | |
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| 0.0079 | 13.0 | 45202 | 0.6117 | 61.61 | 76.52 | 68.26 | 0 | 0.0 | |
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| 0.0244 | 14.0 | 48679 | 0.6191 | 63.78 | 76.44 | 69.54 | 0 | 0.0581 | |
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| 0.0575 | 15.0 | 52156 | 0.6320 | 66.27 | 76.71 | 71.11 | 0 | 0.1161 | |
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| 0.0204 | 16.0 | 55634 | 0.6126 | 67.51 | 76.48 | 71.72 | 0 | 0.0 | |
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| 0.0278 | 17.0 | 59111 | 0.6114 | 67.6 | 76.8 | 71.91 | 0 | 0.0581 | |
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| 0.0219 | 18.0 | 62588 | 0.6184 | 68.84 | 77.14 | 72.75 | 0 | 0.0581 | |
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| 0.01 | 19.0 | 66065 | 0.6197 | 69.62 | 76.77 | 73.02 | 0 | 0.0 | |
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| 0.0423 | 20.0 | 69542 | 0.6204 | 71.01 | 76.89 | 73.83 | 0 | 0.0581 | |
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| 0.0095 | 21.0 | 73019 | 0.6309 | 70.76 | 76.53 | 73.53 | 0 | 0.0581 | |
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| 0.0132 | 22.0 | 76496 | 0.6208 | 71.97 | 76.41 | 74.12 | 0 | 0.2904 | |
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| 0.0148 | 23.0 | 79973 | 0.6307 | 71.86 | 76.61 | 74.16 | 0 | 0.0581 | |
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| 0.0034 | 24.0 | 83451 | 0.6258 | 72.41 | 76.24 | 74.28 | 0 | 0.3484 | |
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| 0.0527 | 25.0 | 86925 | 0.6212 | 72.94 | 75.83 | 74.36 | 0 | 0.4065 | |
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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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