jordyvl commited on
Commit
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Saving best model of baseline_BERT_10K_steps to hub

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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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+ - arxiv_dataset
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: baseline_BERT_10K_steps
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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: arxiv_dataset
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+ type: arxiv_dataset
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+ config: default
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+ split: train
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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: 0.9905994544286106
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+ - name: Precision
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+ type: precision
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+ value: 0.7827298050139275
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+ - name: Recall
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+ type: recall
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+ value: 0.05172572480441785
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+ - name: F1
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+ type: f1
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+ value: 0.09703876370543037
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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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+ # baseline_BERT_10K_steps
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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 arxiv_dataset dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0356
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+ - Accuracy: 0.9906
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+ - Precision: 0.7827
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+ - Recall: 0.0517
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+ - F1: 0.0970
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+ - Hamming: 0.0094
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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: 6
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+ - eval_batch_size: 6
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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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+ - training_steps: 10000
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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 | Precision | Recall | F1 | Hamming |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
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+ | No log | 0.0 | 500 | 0.1602 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.0 | 1000 | 0.0573 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.0 | 1500 | 0.0504 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.01 | 2000 | 0.0492 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.01 | 2500 | 0.0488 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.01 | 3000 | 0.0485 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.01 | 3500 | 0.0477 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.01 | 4000 | 0.0467 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.01 | 4500 | 0.0455 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.01 | 5000 | 0.0442 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.02 | 5500 | 0.0422 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.02 | 6000 | 0.0408 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.02 | 6500 | 0.0394 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 |
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+ | No log | 0.02 | 7000 | 0.0385 | 0.9902 | 1.0 | 0.0011 | 0.0022 | 0.0098 |
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+ | No log | 0.02 | 7500 | 0.0376 | 0.9903 | 0.7949 | 0.0057 | 0.0113 | 0.0097 |
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+ | No log | 0.02 | 8000 | 0.0368 | 0.9903 | 0.8071 | 0.0146 | 0.0287 | 0.0097 |
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+ | No log | 0.03 | 8500 | 0.0363 | 0.9905 | 0.7372 | 0.0465 | 0.0874 | 0.0095 |
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+ | No log | 0.03 | 9000 | 0.0359 | 0.9905 | 0.7811 | 0.0381 | 0.0727 | 0.0095 |
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+ | No log | 0.03 | 9500 | 0.0357 | 0.9906 | 0.8029 | 0.0562 | 0.1051 | 0.0094 |
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+ | 0.0665 | 0.03 | 10000 | 0.0356 | 0.9906 | 0.7827 | 0.0517 | 0.0970 | 0.0094 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
all_results.json ADDED
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+ {
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+ "epoch": 0.03,
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+ "train_loss": 0.066533935546875,
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+ "train_runtime": 6679.0776,
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+ "train_samples_per_second": 8.983,
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+ "train_steps_per_second": 1.497
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+ }
config.json ADDED
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