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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-base-lener-br-finetuned-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: train |
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args: lener_br |
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metrics: |
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- type: precision |
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value: 0.8942967409948542 |
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name: Precision |
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- type: recall |
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value: 0.8969892473118279 |
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name: Recall |
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- type: f1 |
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value: 0.8956409705819198 |
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name: F1 |
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- type: accuracy |
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value: 0.9696009264479559 |
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name: Accuracy |
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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: 0.981178408105048 |
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name: Accuracy |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzNkNTFiM2M3NWNhMjFiZWI0YTg5YjA0NzdhMWZhNjFjNjNkNzU2Njc0YmUxNGJkODNkZjM1MGQ1OTA1MzZjZCIsInZlcnNpb24iOjF9.TFhSrPDOoDWDTWYdOwq2_xNpT-8qOz6sY_ssjyFtSe48yOMEYo4WsPSPye-k65_dC5fRoKkcDaNB5LI3MCpoAg |
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- type: precision |
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value: 0.98709417546121 |
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name: Precision |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDk5ZDNmMGI1YzI1Y2E1MDgyZDc5ZTdmZTdjZDkwNDVhOTlhOWFkMGZkYzMxMzk4MzMxNDk0MzQ2YTI1ZmFmMCIsInZlcnNpb24iOjF9.neTDrpxoUh00ogYYaqMDWKyuJ5Vr4zvtDfe3qL6KaXQ4vwR01OogcRRU95_OPJ5SxeayuwOdwsFeB9VGneE1CQ |
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- type: recall |
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value: 0.9862996055703132 |
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name: Recall |
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verified: true |
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWQ3Y2JiZGFlN2RmNzY3ZjI4ZGYyYTVjMjBmOTQ2YjhiYTIxY2QxM2YyZDllNTc2ZDZhYjFjMTkzNzc5ZjFiZSIsInZlcnNpb24iOjF9.btGMRFJdxbcSeInckLfegVz7-3sBGPB2i70ASv6okG32yAnXEbiQ3MGEF0eyV4UXPvSrYeKac1pJWIViy0eyCQ |
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- type: f1 |
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value: 0.986696730552424 |
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name: F1 |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmYyMjA0ZGM3MjcxMWJjMjUxMDlhODQ1OTE0OTY3ZGNkNTkwZjViMzg0ZTk5ODIxYmQ4MDRhNTRlNmNiZGMzNyIsInZlcnNpb24iOjF9.H9fYIIhKMM2-zOH_2M3YBtfTiTAze3HS3tqxHzJDB6jd5YGB3PMbn6h38KbbTQAVVJZI9jXKYnOZjV-0EjefBQ |
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- type: loss |
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value: 0.144147127866745 |
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name: loss |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmM1ZDE5N2EyZGEyYzYzMmZjZDllZDhmYTgxNjIzODFhN2M2M2IyNWI3Y2IyMDdhOTkzZDA1MTE5NjkyODRlNiIsInZlcnNpb24iOjF9.L_Au7zxnzAtLRljLdlcFL1E-RWlmHty5W4YDMay9wH_PNZaI0X2MK5ifYP0871GHjAcmtk2M_Q-wIW7tHn0KAQ |
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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: 0.9696009264479559 |
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name: Accuracy |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYjBhZGQxYzM3MjY2MDRmNWEyMzdiY2JlYTFjODVkZTg4YzVmYzEwY2ZlNjg1MWZmZjg4MjFkM2NkNjM5MjEzNyIsInZlcnNpb24iOjF9.NS7MqD-lX7_UE79cN4ehs6cpTwaOUUn5UUpojQtmy3jc1JzO1FbJg1yJJRWCHCKzjtfLNMj9SZMoAGclMXV_AQ |
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- type: precision |
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value: 0.974166236103935 |
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name: Precision |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOWJkM2YzMjg3NjAwZTVmN2RjOTBiN2NjMjVmZjgzNzRlNTczOGM5NjQxM2UxMDEwZmFjOTUwOWNiYTRiZDBhNSIsInZlcnNpb24iOjF9.KYe08ccpe08hIRFRj5Pb36ikvbfN_jRfJd5Q90v1YQPLaqaisMhuN1601L6l0BSTT1lKzVbmso1HRUZsVwDACw |
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- type: recall |
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value: 0.9847359110437199 |
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name: Recall |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmYzY2VhODAwZTZlYTQzMmIxNDBkODgwYmIyYTM0YjJlOGE1ZGYwZDQ2Nzc1YjJkYjlhYmVmMjZiZTFhNDI5NSIsInZlcnNpb24iOjF9.ZLCjCyy5W7bHN2fsuxDgGrAPctgpuMJgRWPDXVMLxlZ8wHZisjOks4djo07CZMOu4mG1Eo3Lu-bFcA8-bj0fAQ |
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- type: f1 |
|
value: 0.9794225581044623 |
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name: F1 |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzQ3ZTYzYTFjMmE5YTMwYzA5YTNkZTczNDA3MTI4ZGVkMGVhNWFjMTBjZjgzZjcwMDYxMzM4YWRhMTg2NmM1YiIsInZlcnNpb24iOjF9.xX25-TgY7x6kZxSt1ssxWNP9b6v3oUF8XtLWyzBQHxTXs60RoraAz9isRVkU4CgWKrY81cHhGoNY7G-C26xLAA |
|
- type: loss |
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value: 0.26272761821746826 |
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name: loss |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzE4NmEzMjZlYmM1MzlkNzk5ZDE1M2IzYzNlNmM4YjgwNjRhZGVkZTFmNTBhZTVmOWEyZTVhNGM2MDljZjc2NSIsInZlcnNpb24iOjF9.xt17F4zNWnhlkLrjQv9tcl9ZeY68kr5UKCJhb8dDkwPIGS2u4ojyK8QtbKXO-_QY-X_oQZgdlbvQX4QYVVC4DQ |
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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-base-lener-br-finetuned-lener-br |
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This model is a fine-tuned version of [Luciano/bertimbau-base-finetuned-lener-br](https://huggingface.co/Luciano/bertimbau-base-finetuned-lener-br) on the lener_br dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Precision: 0.8943 |
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- Recall: 0.8970 |
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- F1: 0.8956 |
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- Accuracy: 0.9696 |
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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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| 0.0678 | 1.0 | 1957 | nan | 0.8148 | 0.8882 | 0.8499 | 0.9689 | |
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| 0.0371 | 2.0 | 3914 | nan | 0.8347 | 0.9022 | 0.8671 | 0.9671 | |
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| 0.0242 | 3.0 | 5871 | nan | 0.8491 | 0.8905 | 0.8693 | 0.9716 | |
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| 0.0197 | 4.0 | 7828 | nan | 0.9014 | 0.8772 | 0.8892 | 0.9780 | |
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| 0.0135 | 5.0 | 9785 | nan | 0.8651 | 0.9060 | 0.8851 | 0.9765 | |
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| 0.013 | 6.0 | 11742 | nan | 0.8882 | 0.9054 | 0.8967 | 0.9767 | |
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| 0.0084 | 7.0 | 13699 | nan | 0.8559 | 0.9097 | 0.8820 | 0.9751 | |
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| 0.0069 | 8.0 | 15656 | nan | 0.8916 | 0.8828 | 0.8872 | 0.9696 | |
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| 0.0047 | 9.0 | 17613 | nan | 0.8964 | 0.8931 | 0.8948 | 0.9716 | |
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| 0.0028 | 10.0 | 19570 | nan | 0.8864 | 0.9047 | 0.8955 | 0.9691 | |
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| 0.0023 | 11.0 | 21527 | nan | 0.8860 | 0.9011 | 0.8935 | 0.9693 | |
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| 0.0009 | 12.0 | 23484 | nan | 0.8952 | 0.8987 | 0.8970 | 0.9686 | |
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| 0.0014 | 13.0 | 25441 | nan | 0.8929 | 0.8985 | 0.8957 | 0.9699 | |
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| 0.0025 | 14.0 | 27398 | nan | 0.8914 | 0.8981 | 0.8947 | 0.9700 | |
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| 0.001 | 15.0 | 29355 | nan | 0.8943 | 0.8970 | 0.8956 | 0.9696 | |
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### Framework versions |
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- Transformers 4.21.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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