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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: bert-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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+ - f1
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+ model-index:
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+ - name: ag-news-twitter-76800-bert-base-uncased
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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: F1
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+ type: f1
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+ value: 0.9414991482921289
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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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+ # ag-news-twitter-76800-bert-base-uncased
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ag_news dataset.
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+ It achieves the following results on the evaluation set:
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+ - F1: 0.9415
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+ - Acc: 0.9416
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+ - Loss: 0.5192
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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: 8
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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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+ - lr_scheduler_warmup_ratio: 0.1
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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 | F1 | Acc | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:------:|:------:|:---------------:|
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+ | 0.2328 | 1.0 | 4800 | 0.9289 | 0.9289 | 0.2082 |
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+ | 0.2061 | 2.0 | 9600 | 0.9366 | 0.9367 | 0.2154 |
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+ | 0.1488 | 3.0 | 14400 | 0.9401 | 0.9401 | 0.2181 |
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+ | 0.114 | 4.0 | 19200 | 0.9280 | 0.9275 | 0.3199 |
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+ | 0.0818 | 5.0 | 24000 | 0.9399 | 0.94 | 0.2953 |
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+ | 0.051 | 6.0 | 28800 | 0.9402 | 0.9403 | 0.3828 |
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+ | 0.0413 | 7.0 | 33600 | 0.9404 | 0.9403 | 0.4327 |
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+ | 0.0342 | 8.0 | 38400 | 0.9395 | 0.9395 | 0.4291 |
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+ | 0.0192 | 9.0 | 43200 | 0.9422 | 0.9422 | 0.4170 |
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+ | 0.0204 | 10.0 | 48000 | 0.9374 | 0.9374 | 0.4761 |
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+ | 0.0125 | 11.0 | 52800 | 0.9358 | 0.9359 | 0.5126 |
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+ | 0.0124 | 12.0 | 57600 | 0.9415 | 0.9416 | 0.5192 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ "num_attention_heads": 12,
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "type_vocab_size": 2,
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+ }
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