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N_distilbert_agnews_padding50model

Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: distilbert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - ag_news
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: N_distilbert_agnews_padding50model
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: ag_news
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+ type: ag_news
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+ config: default
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+ split: test
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9418421052631579
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+ ---
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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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+
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+ # N_distilbert_agnews_padding50model
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ag_news dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6732
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+ - Accuracy: 0.9418
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 16
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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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:------:|:---------------:|:--------:|
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+ | 0.1757 | 1.0 | 7500 | 0.1847 | 0.9428 |
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+ | 0.1399 | 2.0 | 15000 | 0.1983 | 0.9439 |
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+ | 0.1196 | 3.0 | 22500 | 0.2251 | 0.9418 |
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+ | 0.0894 | 4.0 | 30000 | 0.2583 | 0.9436 |
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+ | 0.0587 | 5.0 | 37500 | 0.3116 | 0.9425 |
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+ | 0.0404 | 6.0 | 45000 | 0.3567 | 0.9432 |
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+ | 0.0318 | 7.0 | 52500 | 0.4279 | 0.9392 |
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+ | 0.0257 | 8.0 | 60000 | 0.4443 | 0.9407 |
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+ | 0.0212 | 9.0 | 67500 | 0.4974 | 0.9378 |
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+ | 0.0106 | 10.0 | 75000 | 0.4965 | 0.9417 |
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+ | 0.0145 | 11.0 | 82500 | 0.4986 | 0.9433 |
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+ | 0.011 | 12.0 | 90000 | 0.5389 | 0.9392 |
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+ | 0.0121 | 13.0 | 97500 | 0.5671 | 0.9441 |
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+ | 0.0046 | 14.0 | 105000 | 0.6063 | 0.9396 |
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+ | 0.0011 | 15.0 | 112500 | 0.6245 | 0.9414 |
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+ | 0.002 | 16.0 | 120000 | 0.6103 | 0.9426 |
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+ | 0.001 | 17.0 | 127500 | 0.6181 | 0.9426 |
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+ | 0.0017 | 18.0 | 135000 | 0.6401 | 0.9408 |
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+ | 0.0002 | 19.0 | 142500 | 0.6667 | 0.9422 |
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+ | 0.0004 | 20.0 | 150000 | 0.6732 | 0.9418 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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