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# bbc-ner-deberta-large_baseline2_dims

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1481
- Cargo Dimension Precision: 0.7606
- Cargo Dimension Recall: 0.9474
- Cargo Dimension F1: 0.8437
- Cargo Dimension Number: 114
- Cargo Quantity Precision: 0.8079
- Cargo Quantity Recall: 0.8937
- Cargo Quantity F1: 0.8486
- Cargo Quantity Number: 207
- Cargo Requirements Precision: 0.4962
- Cargo Requirements Recall: 0.6535
- Cargo Requirements F1: 0.5641
- Cargo Requirements Number: 202
- Cargo Stowage Factor Precision: 0.8226
- Cargo Stowage Factor Recall: 0.8361
- Cargo Stowage Factor F1: 0.8293
- Cargo Stowage Factor Number: 122
- Cargo Type Precision: 0.7885
- Cargo Type Recall: 0.8183
- Cargo Type F1: 0.8031
- Cargo Type Number: 688
- Cargo Weigh Volume Precision: 0.8528
- Cargo Weigh Volume Recall: 0.9026
- Cargo Weigh Volume F1: 0.8770
- Cargo Weigh Volume Number: 719
- Commission Rate Precision: 0.7955
- Commission Rate Recall: 0.8452
- Commission Rate F1: 0.8196
- Commission Rate Number: 336
- Discharging Port Precision: 0.8706
- Discharging Port Recall: 0.9015
- Discharging Port F1: 0.8858
- Discharging Port Number: 843
- Laycan Date Precision: 0.8260
- Laycan Date Recall: 0.8710
- Laycan Date F1: 0.8479
- Laycan Date Number: 496
- Loading Discharging Terms Precision: 0.7211
- Loading Discharging Terms Recall: 0.7975
- Loading Discharging Terms F1: 0.7574
- Loading Discharging Terms Number: 321
- Loading Port Precision: 0.8906
- Loading Port Recall: 0.9232
- Loading Port F1: 0.9066
- Loading Port Number: 899
- Shipment Terms Precision: 0.6780
- Shipment Terms Recall: 0.6780
- Shipment Terms F1: 0.6780
- Shipment Terms Number: 118
- Vessel Requirements Precision: 0.3786
- Vessel Requirements Recall: 0.5132
- Vessel Requirements F1: 0.4358
- Vessel Requirements Number: 76
- Overall Precision: 0.8041
- Overall Recall: 0.8598
- Overall F1: 0.8310
- Overall Accuracy: 0.9688

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cargo Dimension Precision | Cargo Dimension Recall | Cargo Dimension F1 | Cargo Dimension Number | Cargo Quantity Precision | Cargo Quantity Recall | Cargo Quantity F1 | Cargo Quantity Number | Cargo Requirements Precision | Cargo Requirements Recall | Cargo Requirements F1 | Cargo Requirements Number | Cargo Stowage Factor Precision | Cargo Stowage Factor Recall | Cargo Stowage Factor F1 | Cargo Stowage Factor Number | Cargo Type Precision | Cargo Type Recall | Cargo Type F1 | Cargo Type Number | Cargo Weigh Volume Precision | Cargo Weigh Volume Recall | Cargo Weigh Volume F1 | Cargo Weigh Volume Number | Commission Rate Precision | Commission Rate Recall | Commission Rate F1 | Commission Rate Number | Discharging Port Precision | Discharging Port Recall | Discharging Port F1 | Discharging Port Number | Laycan Date Precision | Laycan Date Recall | Laycan Date F1 | Laycan Date Number | Loading Discharging Terms Precision | Loading Discharging Terms Recall | Loading Discharging Terms F1 | Loading Discharging Terms Number | Loading Port Precision | Loading Port Recall | Loading Port F1 | Loading Port Number | Shipment Terms Precision | Shipment Terms Recall | Shipment Terms F1 | Shipment Terms Number | Vessel Requirements Precision | Vessel Requirements Recall | Vessel Requirements F1 | Vessel Requirements Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:------------------------------:|:---------------------------:|:-----------------------:|:---------------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-----------------------------------:|:--------------------------------:|:----------------------------:|:--------------------------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.4476        | 1.0   | 119  | 0.1523          | 0.6169                    | 0.8333                 | 0.7090             | 114                    | 0.7087                   | 0.8696                | 0.7809            | 207                   | 0.3007                       | 0.4257                    | 0.3525                | 202                       | 0.6284                         | 0.7623                      | 0.6889                  | 122                         | 0.6478               | 0.6308            | 0.6392        | 688               | 0.6983                       | 0.8178                    | 0.7534                | 719                       | 0.7099                    | 0.7649                 | 0.7364             | 336                    | 0.7212                     | 0.8683                  | 0.7879              | 843                     | 0.7482                | 0.8266             | 0.7854         | 496                | 0.5669                              | 0.6729                           | 0.6154                       | 321                              | 0.8280                 | 0.8565              | 0.8420          | 899                 | 0.6556                   | 0.5                   | 0.5673            | 118                   | 0.0658                        | 0.0658                     | 0.0658                 | 76                         | 0.6819            | 0.7635         | 0.7204     | 0.9581           |
| 0.132         | 2.0   | 239  | 0.1438          | 0.6471                    | 0.8684                 | 0.7416             | 114                    | 0.7212                   | 0.9372                | 0.8151            | 207                   | 0.2857                       | 0.4455                    | 0.3482                | 202                       | 0.7083                         | 0.8361                      | 0.7669                  | 122                         | 0.6586               | 0.8270            | 0.7332        | 688               | 0.7191                       | 0.8901                    | 0.7955                | 719                       | 0.7863                    | 0.8542                 | 0.8188             | 336                    | 0.7639                     | 0.8944                  | 0.8240              | 843                     | 0.7370                | 0.8589             | 0.7933         | 496                | 0.5497                              | 0.7757                           | 0.6434                       | 321                              | 0.8533                 | 0.8932              | 0.8728          | 899                 | 0.5669                   | 0.6102                | 0.5878            | 118                   | 0.216                         | 0.3553                     | 0.2687                 | 76                         | 0.6943            | 0.8387         | 0.7597     | 0.9579           |
| 0.1022        | 3.0   | 358  | 0.1217          | 0.7574                    | 0.9035                 | 0.8240             | 114                    | 0.8087                   | 0.8986                | 0.8513            | 207                   | 0.4081                       | 0.5495                    | 0.4684                | 202                       | 0.75                           | 0.8361                      | 0.7907                  | 122                         | 0.7301               | 0.8140            | 0.7698        | 688               | 0.8132                       | 0.8720                    | 0.8416                | 719                       | 0.7983                    | 0.8482                 | 0.8225             | 336                    | 0.8123                     | 0.9087                  | 0.8578              | 843                     | 0.7901                | 0.8730             | 0.8295         | 496                | 0.7583                              | 0.7819                           | 0.7699                       | 321                              | 0.8783                 | 0.9232              | 0.9002          | 899                 | 0.7596                   | 0.6695                | 0.7117            | 118                   | 0.3529                        | 0.4737                     | 0.4045                 | 76                         | 0.7744            | 0.8498         | 0.8103     | 0.9677           |
| 0.0802        | 4.0   | 478  | 0.1291          | 0.7589                    | 0.9386                 | 0.8392             | 114                    | 0.8097                   | 0.8841                | 0.8453            | 207                   | 0.4566                       | 0.5990                    | 0.5182                | 202                       | 0.8347                         | 0.8279                      | 0.8313                  | 122                         | 0.7710               | 0.7733            | 0.7721        | 688               | 0.8015                       | 0.8818                    | 0.8397                | 719                       | 0.8203                    | 0.8423                 | 0.8311             | 336                    | 0.8449                     | 0.9110                  | 0.8767              | 843                     | 0.8252                | 0.8851             | 0.8541         | 496                | 0.7202                              | 0.7539                           | 0.7367                       | 321                              | 0.8637                 | 0.9232              | 0.8925          | 899                 | 0.7404                   | 0.6525                | 0.6937            | 118                   | 0.4359                        | 0.4474                     | 0.4416                 | 76                         | 0.7912            | 0.8463         | 0.8179     | 0.9683           |
| 0.0733        | 5.0   | 597  | 0.1269          | 0.7347                    | 0.9474                 | 0.8276             | 114                    | 0.7975                   | 0.9130                | 0.8514            | 207                   | 0.4306                       | 0.6139                    | 0.5061                | 202                       | 0.8062                         | 0.8525                      | 0.8287                  | 122                         | 0.7564               | 0.8169            | 0.7855        | 688               | 0.8142                       | 0.8901                    | 0.8505                | 719                       | 0.8184                    | 0.8452                 | 0.8316             | 336                    | 0.8760                     | 0.9051                  | 0.8903              | 843                     | 0.8180                | 0.8790             | 0.8474         | 496                | 0.7303                              | 0.8100                           | 0.7681                       | 321                              | 0.8747                 | 0.9321              | 0.9025          | 899                 | 0.6231                   | 0.6864                | 0.6532            | 118                   | 0.3407                        | 0.4079                     | 0.3713                 | 76                         | 0.7870            | 0.8598         | 0.8218     | 0.9681           |
| 0.0541        | 6.0   | 717  | 0.1299          | 0.7379                    | 0.9386                 | 0.8263             | 114                    | 0.7899                   | 0.9082                | 0.8449            | 207                   | 0.4330                       | 0.6238                    | 0.5112                | 202                       | 0.8095                         | 0.8361                      | 0.8226                  | 122                         | 0.7681               | 0.8183            | 0.7924        | 688               | 0.7916                       | 0.8929                    | 0.8392                | 719                       | 0.8182                    | 0.8571                 | 0.8372             | 336                    | 0.8491                     | 0.9075                  | 0.8773              | 843                     | 0.8056                | 0.8690             | 0.8361         | 496                | 0.6981                              | 0.7850                           | 0.7390                       | 321                              | 0.8828                 | 0.9388              | 0.9100          | 899                 | 0.6991                   | 0.6695                | 0.6840            | 118                   | 0.38                          | 0.5                        | 0.4318                 | 76                         | 0.7815            | 0.8607         | 0.8192     | 0.9676           |
| 0.0463        | 7.0   | 836  | 0.1311          | 0.7626                    | 0.9298                 | 0.8379             | 114                    | 0.8243                   | 0.8841                | 0.8531            | 207                   | 0.4731                       | 0.6089                    | 0.5325                | 202                       | 0.7895                         | 0.8607                      | 0.8235                  | 122                         | 0.7875               | 0.7863            | 0.7869        | 688               | 0.8366                       | 0.8901                    | 0.8625                | 719                       | 0.8067                    | 0.8571                 | 0.8312             | 336                    | 0.8928                     | 0.8992                  | 0.8960              | 843                     | 0.8314                | 0.8649             | 0.8478         | 496                | 0.7672                              | 0.8006                           | 0.7835                       | 321                              | 0.9013                 | 0.9143              | 0.9078          | 899                 | 0.6529                   | 0.6695                | 0.6611            | 118                   | 0.3608                        | 0.4605                     | 0.4046                 | 76                         | 0.8096            | 0.8493         | 0.8289     | 0.9686           |
| 0.0434        | 8.0   | 956  | 0.1430          | 0.7448                    | 0.9474                 | 0.8340             | 114                    | 0.7957                   | 0.9034                | 0.8462            | 207                   | 0.4765                       | 0.6535                    | 0.5511                | 202                       | 0.7863                         | 0.8443                      | 0.8142                  | 122                         | 0.7916               | 0.8227            | 0.8068        | 688               | 0.8274                       | 0.8999                    | 0.8621                | 719                       | 0.8141                    | 0.8601                 | 0.8365             | 336                    | 0.8727                     | 0.9027                  | 0.8875              | 843                     | 0.8241                | 0.8690             | 0.8459         | 496                | 0.7298                              | 0.8162                           | 0.7706                       | 321                              | 0.8943                 | 0.9132              | 0.9037          | 899                 | 0.5797                   | 0.6780                | 0.6250            | 118                   | 0.3491                        | 0.4868                     | 0.4066                 | 76                         | 0.7963            | 0.8605         | 0.8271     | 0.9681           |
| 0.0373        | 9.0   | 1075 | 0.1435          | 0.75                      | 0.9474                 | 0.8372             | 114                    | 0.8017                   | 0.8986                | 0.8474            | 207                   | 0.4815                       | 0.6436                    | 0.5508                | 202                       | 0.8254                         | 0.8525                      | 0.8387                  | 122                         | 0.7762               | 0.8169            | 0.7960        | 688               | 0.8409                       | 0.9040                    | 0.8713                | 719                       | 0.8011                    | 0.8512                 | 0.8254             | 336                    | 0.8648                     | 0.8956                  | 0.8800              | 843                     | 0.8267                | 0.875              | 0.8501         | 496                | 0.7227                              | 0.8037                           | 0.7611                       | 321                              | 0.8874                 | 0.9288              | 0.9076          | 899                 | 0.6349                   | 0.6780                | 0.6557            | 118                   | 0.3645                        | 0.5132                     | 0.4262                 | 76                         | 0.7969            | 0.8611         | 0.8278     | 0.9686           |
| 0.0348        | 9.96  | 1190 | 0.1481          | 0.7606                    | 0.9474                 | 0.8437             | 114                    | 0.8079                   | 0.8937                | 0.8486            | 207                   | 0.4962                       | 0.6535                    | 0.5641                | 202                       | 0.8226                         | 0.8361                      | 0.8293                  | 122                         | 0.7885               | 0.8183            | 0.8031        | 688               | 0.8528                       | 0.9026                    | 0.8770                | 719                       | 0.7955                    | 0.8452                 | 0.8196             | 336                    | 0.8706                     | 0.9015                  | 0.8858              | 843                     | 0.8260                | 0.8710             | 0.8479         | 496                | 0.7211                              | 0.7975                           | 0.7574                       | 321                              | 0.8906                 | 0.9232              | 0.9066          | 899                 | 0.6780                   | 0.6780                | 0.6780            | 118                   | 0.3786                        | 0.5132                     | 0.4358                 | 76                         | 0.8041            | 0.8598         | 0.8310     | 0.9688           |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/deberta-v3-large", "model-index": [{"name": "bbc-ner-deberta-large_baseline2_dims", "results": []}]}
transformers tensorboard safetensors deberta-v2 token-classification generated_from_trainer base_model:microsoft/deberta-v3-large license:mit autotrain_compatible endpoints_compatible region:us