transformers safetensors mbart text2text-generation en nl es base_model:facebook/mbart-large-cc25 autotrain_compatible endpoints_compatible region:us
---
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
