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Saving model gmra_distilbert/distilbert-base-uncased-finetuned-sst-2-english_08112024T110433

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: distilbert-base-uncased-finetuned-sst-2-english_08112024T110433
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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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+ # distilbert-base-uncased-finetuned-sst-2-english_08112024T110433
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+
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+ This model is a fine-tuned version of [distilbert/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4561
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+ - F1: 0.8591
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+ - Learning Rate: 0.0
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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: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 600
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+ - num_epochs: 20
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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 | F1 | Rate |
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+ |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.9942 | 86 | 1.8025 | 0.1776 | 0.0000 |
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+ | No log | 2.0 | 173 | 1.7296 | 0.1902 | 0.0000 |
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+ | No log | 2.9942 | 259 | 1.6400 | 0.3649 | 0.0000 |
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+ | No log | 4.0 | 346 | 1.4873 | 0.4157 | 0.0000 |
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+ | No log | 4.9942 | 432 | 1.2812 | 0.5119 | 0.0000 |
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+ | 1.5846 | 6.0 | 519 | 1.0792 | 0.5668 | 0.0000 |
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+ | 1.5846 | 6.9942 | 605 | 0.9450 | 0.6226 | 1e-05 |
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+ | 1.5846 | 8.0 | 692 | 0.8238 | 0.6836 | 0.0000 |
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+ | 1.5846 | 8.9942 | 778 | 0.7274 | 0.7374 | 0.0000 |
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+ | 1.5846 | 10.0 | 865 | 0.6411 | 0.7734 | 0.0000 |
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+ | 1.5846 | 10.9942 | 951 | 0.6020 | 0.7822 | 0.0000 |
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+ | 0.7489 | 12.0 | 1038 | 0.5470 | 0.8157 | 0.0000 |
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+ | 0.7489 | 12.9942 | 1124 | 0.5161 | 0.8299 | 0.0000 |
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+ | 0.7489 | 14.0 | 1211 | 0.4952 | 0.8454 | 0.0000 |
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+ | 0.7489 | 14.9942 | 1297 | 0.4768 | 0.8518 | 0.0000 |
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+ | 0.7489 | 16.0 | 1384 | 0.4664 | 0.8546 | 0.0000 |
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+ | 0.7489 | 16.9942 | 1470 | 0.4665 | 0.8565 | 0.0000 |
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+ | 0.3329 | 18.0 | 1557 | 0.4561 | 0.8591 | 5e-07 |
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+ | 0.3329 | 18.9942 | 1643 | 0.4578 | 0.8585 | 1e-07 |
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+ | 0.3329 | 19.8844 | 1720 | 0.4579 | 0.8584 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.1.0
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+ - Tokenizers 0.19.1
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