|
--- |
|
base_model: facebook/mbart-large-cc25 |
|
language: |
|
- en |
|
- nl |
|
- es |
|
--- |
|
|
|
# EN, ES and NL to AMR parsing |
|
|
|
This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6363 |
|
- Smatch Precision: 75.39 |
|
- Smatch Recall: 77.67 |
|
- Smatch Fscore: 76.51 |
|
- Smatch Unparsable: 0 |
|
- Percent Not Recoverable: 0.2129 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 5e-05 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 25 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Smatch Precision | Smatch Recall | Smatch Fscore | Smatch Unparsable | Percent Not Recoverable | |
|
|:-------------:|:-----:|:------:|:---------------:|:----------------:|:-------------:|:-------------:|:-----------------:|:-----------------------:| |
|
| 0.3131 | 1.0 | 10431 | 1.5867 | 25.55 | 66.9 | 36.97 | 0 | 0.0194 | |
|
| 0.0897 | 2.0 | 20862 | 1.0779 | 36.21 | 72.1 | 48.2 | 0 | 0.0968 | |
|
| 0.1392 | 3.0 | 31294 | 0.7726 | 42.78 | 75.64 | 54.65 | 0 | 0.1936 | |
|
| 0.085 | 4.0 | 41725 | 0.7040 | 46.38 | 76.85 | 57.85 | 0 | 0.0774 | |
|
| 0.0008 | 5.0 | 52156 | 0.6874 | 47.47 | 76.12 | 58.47 | 0 | 0.1161 | |
|
| 0.003 | 6.0 | 62588 | 0.6477 | 53.05 | 77.36 | 62.94 | 0 | 0.1742 | |
|
| 0.0306 | 7.0 | 73019 | 0.6230 | 52.01 | 78.19 | 62.47 | 0 | 0.0968 | |
|
| 0.0176 | 8.0 | 83451 | 0.6139 | 52.78 | 78.53 | 63.13 | 0 | 0.2129 | |
|
| 0.0004 | 9.0 | 93882 | 0.6737 | 58.01 | 77.55 | 66.37 | 0 | 0.1355 | |
|
| 0.0018 | 10.0 | 104313 | 0.6187 | 58.99 | 77.99 | 67.17 | 0 | 0.1161 | |
|
| 0.0188 | 11.0 | 114745 | 0.6119 | 62.35 | 78.01 | 69.31 | 0 | 0.1161 | |
|
| 0.0055 | 12.0 | 125176 | 0.6455 | 62.08 | 79.07 | 69.55 | 0 | 0.0774 | |
|
| 0.0555 | 13.0 | 135607 | 0.6502 | 62.35 | 78.17 | 69.37 | 0 | 0.1355 | |
|
| 0.0041 | 14.0 | 146039 | 0.6509 | 65.88 | 78.31 | 71.56 | 0 | 0.1742 | |
|
| 0.0064 | 15.0 | 156470 | 0.6771 | 66.98 | 78.33 | 72.21 | 0 | 0.1355 | |
|
| 0.0031 | 16.0 | 166902 | 0.6361 | 68.12 | 78.66 | 73.01 | 0 | 0.0774 | |
|
| 0.0131 | 17.0 | 177333 | 0.6390 | 69.49 | 78.66 | 73.79 | 0 | 0.0968 | |
|
| 0.0067 | 18.0 | 187764 | 0.6933 | 69.67 | 78.4 | 73.77 | 0 | 0.1549 | |
|
| 0.0267 | 19.0 | 198196 | 0.6558 | 70.64 | 78.71 | 74.46 | 0 | 0.0774 | |
|
| 0.0146 | 20.0 | 208627 | 0.6574 | 71.23 | 78.93 | 74.88 | 0 | 0.1161 | |
|
| 0.0025 | 21.0 | 219058 | 0.6781 | 71.88 | 78.28 | 74.94 | 0 | 0.1936 | |
|
| 0.0044 | 22.0 | 229490 | 0.6491 | 73.08 | 78.57 | 75.72 | 0 | 0.1161 | |
|
| 0.0234 | 23.0 | 239921 | 0.6458 | 74.02 | 78.33 | 76.12 | 0 | 0.1549 | |
|
| 0.0001 | 24.0 | 250353 | 0.6485 | 74.58 | 77.98 | 76.24 | 0 | 0.2129 | |
|
| 0.0448 | 25.0 | 260775 | 0.6363 | 75.39 | 77.67 | 76.51 | 0 | 0.2129 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0.dev0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.2 |
|
- Tokenizers 0.13.3 |
|
|
