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README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: distilhubert-finetuned-pulse
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+ results: []
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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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+ # distilhubert-finetuned-pulse
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+
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+ This model was trained from scratch on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6143
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+ - Accuracy: 0.7143
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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: 5e-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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 15
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+ - mixed_precision_training: Native AMP
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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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+ | 0.6972 | 1.0 | 31 | 0.6880 | 0.7143 |
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+ | 0.703 | 2.0 | 62 | 0.6044 | 0.7143 |
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+ | 0.6737 | 3.0 | 93 | 0.6217 | 0.7143 |
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+ | 0.6756 | 4.0 | 124 | 0.6400 | 0.7143 |
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+ | 0.6557 | 5.0 | 155 | 0.6213 | 0.7143 |
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+ | 0.6778 | 6.0 | 186 | 0.6109 | 0.7143 |
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+ | 0.6884 | 7.0 | 217 | 0.6415 | 0.7143 |
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+ | 0.6364 | 8.0 | 248 | 0.6205 | 0.7143 |
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+ | 0.6506 | 9.0 | 279 | 0.6171 | 0.7143 |
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+ | 0.675 | 10.0 | 310 | 0.6139 | 0.7143 |
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+ | 0.7018 | 11.0 | 341 | 0.6145 | 0.7143 |
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+ | 0.6766 | 12.0 | 372 | 0.6099 | 0.7143 |
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+ | 0.6493 | 13.0 | 403 | 0.6131 | 0.7143 |
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+ | 0.6482 | 14.0 | 434 | 0.6138 | 0.7143 |
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+ | 0.8036 | 15.0 | 465 | 0.6143 | 0.7143 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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