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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: judy93536/distilroberta-rbm231k-ep20-op40
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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: distilroberta-rbm231k-ep20-op40-news_api_all_5p1k
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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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+ # distilroberta-rbm231k-ep20-op40-news_api_all_5p1k
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+
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+ This model is a fine-tuned version of [judy93536/distilroberta-rbm231k-ep20-op40](https://huggingface.co/judy93536/distilroberta-rbm231k-ep20-op40) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2430
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+ - Accuracy: 0.9207
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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: 5.53335054745316e-07
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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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+ - lr_scheduler_warmup_ratio: 0.4
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+ - num_epochs: 30
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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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+ | No log | 1.0 | 256 | 1.0947 | 0.3503 |
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+ | 1.0947 | 2.0 | 512 | 1.0886 | 0.4100 |
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+ | 1.0947 | 3.0 | 768 | 1.0783 | 0.4403 |
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+ | 1.0814 | 4.0 | 1024 | 1.0618 | 0.4569 |
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+ | 1.0814 | 5.0 | 1280 | 1.0324 | 0.4501 |
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+ | 1.048 | 6.0 | 1536 | 0.9890 | 0.4795 |
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+ | 1.048 | 7.0 | 1792 | 0.9498 | 0.5068 |
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+ | 0.9796 | 8.0 | 2048 | 0.9066 | 0.5724 |
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+ | 0.9796 | 9.0 | 2304 | 0.8510 | 0.6468 |
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+ | 0.8954 | 10.0 | 2560 | 0.7850 | 0.6840 |
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+ | 0.8954 | 11.0 | 2816 | 0.7160 | 0.7094 |
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+ | 0.7824 | 12.0 | 3072 | 0.6495 | 0.7495 |
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+ | 0.7824 | 13.0 | 3328 | 0.5894 | 0.7818 |
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+ | 0.6548 | 14.0 | 3584 | 0.5305 | 0.8151 |
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+ | 0.6548 | 15.0 | 3840 | 0.4613 | 0.8620 |
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+ | 0.5446 | 16.0 | 4096 | 0.3921 | 0.8836 |
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+ | 0.5446 | 17.0 | 4352 | 0.3424 | 0.8933 |
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+ | 0.4323 | 18.0 | 4608 | 0.3111 | 0.9012 |
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+ | 0.4323 | 19.0 | 4864 | 0.2838 | 0.9070 |
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+ | 0.3524 | 20.0 | 5120 | 0.2739 | 0.9100 |
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+ | 0.3524 | 21.0 | 5376 | 0.2674 | 0.9090 |
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+ | 0.3148 | 22.0 | 5632 | 0.2583 | 0.9119 |
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+ | 0.3148 | 23.0 | 5888 | 0.2517 | 0.9139 |
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+ | 0.2931 | 24.0 | 6144 | 0.2496 | 0.9159 |
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+ | 0.2931 | 25.0 | 6400 | 0.2451 | 0.9159 |
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+ | 0.2703 | 26.0 | 6656 | 0.2443 | 0.9178 |
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+ | 0.2703 | 27.0 | 6912 | 0.2435 | 0.9198 |
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+ | 0.2649 | 28.0 | 7168 | 0.2424 | 0.9198 |
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+ | 0.2649 | 29.0 | 7424 | 0.2431 | 0.9207 |
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+ | 0.2607 | 30.0 | 7680 | 0.2430 | 0.9207 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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