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--- |
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language: |
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- pt |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- lener_br |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model_index: |
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- name: bertimbau-large-lener_br |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: lener_br |
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type: lener_br |
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args: lener_br |
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metric: |
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name: Accuracy |
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type: accuracy |
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value: 0.9801301293674859 |
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base_model: neuralmind/bert-large-portuguese-cased |
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model-index: |
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- name: Luciano/bertimbau-large-lener_br |
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results: |
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- task: |
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type: token-classification |
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name: Token Classification |
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dataset: |
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name: lener_br |
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type: lener_br |
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config: lener_br |
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split: test |
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metrics: |
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- type: accuracy |
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value: 0.9840898731012984 |
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name: Accuracy |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTcwYjYxOGIzOGEwNjc4NzdkZjJjNGJhYTkzOTY4NmM5MWU0YjIxN2EwNmI4M2E0ZDkwYjUzYTk1NzYwOWYwNyIsInZlcnNpb24iOjF9.AZ4Xkl2_oUMeUxmB-Me7pdDwvQj6Y-6W2KvH6_5mkKuVnT551ffAtBbj8H9ruDvqE4aTlIT0eqrkgHUgcHP1Bg |
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- type: precision |
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value: 0.9895415357344292 |
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name: Precision |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTBhMjRmNDZlMGRiZDJhNjg0ZWVhNzQzMzYzMTQ4MDY2ODEwNzcwYTgwYmEyZDExZmI0OWQ0N2Q5NzdjZDM2OCIsInZlcnNpb24iOjF9.50xubvWSuT0EDjsj-Ox0dFvsmsFQhCDojB15PzynBJBd2PsLOG2eKqWdFYV1iXNnOTum3xCFGKKSE8dvyK6GBQ |
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- type: recall |
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value: 0.9885856878370763 |
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name: Recall |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTA4NzRkMzIwYzdhNmRlODg1YjI3MzA5NmQ5Yjk3NzMzZmQ4MDJjMWRlYzQ1NWNkZjA0MGQ2OTBiMWVlYjdiOCIsInZlcnNpb24iOjF9.5L9WHAEZIiM_rXqIu2kEVU-7Hed3oEi5IO_ulcEDJO-r4KQVXS9X4Rat5FSAjdWSRV_vnvM9Nc7LiOh738WzBA |
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- type: f1 |
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value: 0.9890633808488363 |
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name: F1 |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjIzYzllZWFjZmExN2Q2NDM4ZWY3YjMxZDNiZWFjNzU0ODcwYTBkNTU0ZWExYzM3YjI2MjQ4MTMxOTM5ODdhMyIsInZlcnNpb24iOjF9.tTxenqEcrfQMSbo53mewRPc4oDectJEKfzZyj_mChtQ-K41miMd1n_gNCT-zdT3u1wb5cc7nwgP-Mggo4Q6MAQ |
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- type: loss |
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value: 0.10151929408311844 |
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name: loss |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYmZkM2YzZmJmOGY0MDI0YzI0ZGQyYWM0YTU1YWQ3NDI3M2UxZjU3NjM0MzljODMwMTAyYzU4YWNmZTRhNGM3ZSIsInZlcnNpb24iOjF9.dF2SD2-HEHepUpbmgrndTM42MQ1mtMuuTgwqyv0cO_ZHlqRRQfyZtgLMlf8_5DwpPRKw_F3wwXLRETbL-5LJCw |
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- task: |
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type: token-classification |
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name: Token Classification |
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dataset: |
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name: lener_br |
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type: lener_br |
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config: lener_br |
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split: validation |
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metrics: |
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- type: accuracy |
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value: 0.9801301293674859 |
|
name: Accuracy |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYWY1M2Q5YzIxYzQ3NTU5YzQyMjUwNWY3MWNkMjJlMGM2YzkwMTdhZGM3NmYxZmVjZDc1N2NkMjBhNDEwMzIyOCIsInZlcnNpb24iOjF9.Mtp2ZBdksTfCQJEFiyLt4pILPH7RE8CXodYNcL8ydc7lTTwn5PiGdnglA7GJcd9HqxOU8UsVyaGzxFkjZGkGDw |
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- type: precision |
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value: 0.9864285473144053 |
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name: Precision |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzc1M2NjNTFhNjZiNDU5NzQyZDYzOWViNGFhNzdlMGU4ODNhNDMxMWE1ZjIwZGIzOTIxNDAxZDcwNDM2MGNjYiIsInZlcnNpb24iOjF9.59674wBNKLrL5DC1vfPdEzpCiXRnhilpvnylmzkvLmBrJrZdy-rTP4AXir62BoUEyEZ6zMPRRNOYI9fduwfnBQ |
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- type: recall |
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value: 0.9845505854603656 |
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name: Recall |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDc4YjVlYmQ1ZjllNzU3M2ZkN2QxNzI1MGZhMzhkMDNmMjNjODM3NGMzYzY2OGM1NGJmMDA4ZGUwM2RkMGY5MyIsInZlcnNpb24iOjF9.tYvf8mJ0XUmH3mZ0NIMdrXY5a93-2H9u5Ak6heCMBpmHhvgL8k_9y25cRmLeWoh9apsCIS6lQDpHlsJBXdhGDg |
|
- type: f1 |
|
value: 0.9854886717201953 |
|
name: F1 |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMGY4YmJjYzkyNzU1ZDQ3MWFmZTY4MWU1OTg4NTRmOTIwM2I3NzdkYWI2YmNlYjdjODQyMmE2N2M5MDQ5MDEyYiIsInZlcnNpb24iOjF9.FxRrhWWfyA-oIXb5zzHO3-VboU6iFcnRc_kVPgLaOcyk8p5jIfV-egDHrql6e-h-6iS8xTDFV8fxIoq-kboRDQ |
|
- type: loss |
|
value: 0.11984097212553024 |
|
name: loss |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZGE2NzM4MjE1MmU1ZTU4ZTU1NjAyYzk2YzdlNTUxOTAyZjdiMTkxYmZlMzExYmUwOTRhMTA3NzcwYWM2NzgxMiIsInZlcnNpb24iOjF9.PAlnc-tkJ7DEp9-qIR7KpYK9Yzy-umlhwKMH8bq1p-Gxf5pSIL_AtG8eP-JrbH71pJLYaBxSeeRHXWhIT-jBBA |
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- task: |
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type: token-classification |
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name: Token Classification |
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dataset: |
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name: lener_br |
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type: lener_br |
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config: lener_br |
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split: train |
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metrics: |
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- type: accuracy |
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value: 0.9989004979420315 |
|
name: Accuracy |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTMwYWI4ZDdiZmNkYWYzNDNhZWI4MmNhNDE5MjRmMjRjYTZjYjI1YTllMzMyMDMxMTBmN2YwN2QxMmE3Y2ViYyIsInZlcnNpb24iOjF9.yihlFpU8AYKMsa4f_7P2J-JYifENGVm0nXGwKcvOV_axvv-Gj-Q-E93j0sHnb3TXTpTlJBgQ0ckBDh4Sohq3AQ |
|
- type: precision |
|
value: 0.9991129612205654 |
|
name: Precision |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzM3MTQ3ODU3MzBiY2RmNGVhMmQ2YTUzODlkZTk1M2EyOGU4Y2I5ZDI0ZGI5YWQ1YWQ4NDE2NGI1ZjYxNTM1YSIsInZlcnNpb24iOjF9.nnTSkmuvHdYFhXUofIEtjIaEveJCBlMrlmwSwRLojcXYvoaZWNFkWI8wSkQP0iDdDhKuEaZYkRc4kJ-Xd4_TCw |
|
- type: recall |
|
value: 0.9993219071519783 |
|
name: Recall |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTA1NGMzOGMwMWQ3Yzk0ZmY4YmYxZjVjODQwMDA1ZjgxNjQ2Y2IxMmIxYWJjOTJhOGQ2NjRlOTRjOTkzYjkwMyIsInZlcnNpb24iOjF9.2YuShB7RWqO6WeR9RCePUcDPv-Ho-6pYeFXmmnnYmW88BRN5jHSrJTWPXMxigVRPBHjU5LlE8j2EK3-IsNviCQ |
|
- type: f1 |
|
value: 0.9992174232631231 |
|
name: F1 |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTE2YmMzMTI3MzQ5MTRmZGQ3NTdhODc3ZGI0MjIyOWMzZTc1MGQ4ZjVkY2JhYjYyM2I1NmI2MWI1OTZkYjViMyIsInZlcnNpb24iOjF9.TJkpCVwoTHFSwD8ckgn1dvD-H5HscuFmtsjEFYNVDZPnfm2PN7b45vZxNvWiK7L6ZVFW2fXbwgNJmMapuoeMCw |
|
- type: loss |
|
value: 0.0037613145541399717 |
|
name: loss |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZmUxYWU2ODFkOTQ4NjIyODQ1NTU0NDQ2ZjhmYjExZmE3ZDNkZDBjNmIwY2JlNGRlNGZhOGExMDQ1MjA5Nzk0MiIsInZlcnNpb24iOjF9.ES0Kzjz3vvY5HedqYQzZafOPzQSbdWIbsdmft136SqIwb_-rZe-qQ38lveUYuUArP7NHk0wgo3NIkC6LqIsVAw |
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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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# bertimbau-large-lener_br |
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This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the lener_br dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1271 |
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- Precision: 0.8965 |
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- Recall: 0.9198 |
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- F1: 0.9080 |
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- Accuracy: 0.9801 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.0674 | 1.0 | 1957 | 0.1349 | 0.7617 | 0.8710 | 0.8127 | 0.9594 | |
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| 0.0443 | 2.0 | 3914 | 0.1867 | 0.6862 | 0.9194 | 0.7858 | 0.9575 | |
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| 0.0283 | 3.0 | 5871 | 0.1185 | 0.8206 | 0.8766 | 0.8477 | 0.9678 | |
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| 0.0226 | 4.0 | 7828 | 0.1405 | 0.8072 | 0.8978 | 0.8501 | 0.9708 | |
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| 0.0141 | 5.0 | 9785 | 0.1898 | 0.7224 | 0.9194 | 0.8090 | 0.9629 | |
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| 0.01 | 6.0 | 11742 | 0.1655 | 0.9062 | 0.8856 | 0.8958 | 0.9741 | |
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| 0.012 | 7.0 | 13699 | 0.1271 | 0.8965 | 0.9198 | 0.9080 | 0.9801 | |
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| 0.0091 | 8.0 | 15656 | 0.1919 | 0.8890 | 0.8886 | 0.8888 | 0.9719 | |
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| 0.0042 | 9.0 | 17613 | 0.1725 | 0.8977 | 0.8985 | 0.8981 | 0.9744 | |
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| 0.0043 | 10.0 | 19570 | 0.1530 | 0.8878 | 0.9034 | 0.8955 | 0.9761 | |
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| 0.0042 | 11.0 | 21527 | 0.1635 | 0.8792 | 0.9108 | 0.8947 | 0.9774 | |
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| 0.0033 | 12.0 | 23484 | 0.2009 | 0.8155 | 0.9138 | 0.8619 | 0.9719 | |
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| 0.0008 | 13.0 | 25441 | 0.1766 | 0.8737 | 0.9135 | 0.8932 | 0.9755 | |
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| 0.0005 | 14.0 | 27398 | 0.1868 | 0.8616 | 0.9129 | 0.8865 | 0.9743 | |
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| 0.0014 | 15.0 | 29355 | 0.1910 | 0.8694 | 0.9101 | 0.8893 | 0.9746 | |
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### Framework versions |
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- Transformers 4.8.2 |
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- Pytorch 1.9.0+cu102 |
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- Datasets 1.9.0 |
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- Tokenizers 0.10.3 |
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