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climate-fever-plus-RoBERTa

Text Classification
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Safetensors
roberta
fact-checking
climate
text entailment
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climate_verfication_model

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Files changed (9) hide show
  1. README.md +201 -0
  2. config.json +38 -0
  3. merges.txt +0 -0
  4. model.safetensors +3 -0
  5. special_tokens_map.json +15 -0
  6. tokenizer.json +0 -0
  7. tokenizer_config.json +57 -0
  8. training_args.bin +3 -0
  9. vocab.json +0 -0
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: roberta-base
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: results
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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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+ # results
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7998
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+ - Accuracy: 0.7023
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+ - Precision: 0.7144
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+ - Recall: 0.7023
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+ - F1: 0.7065
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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: 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_steps: 500
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+ - num_epochs: 5
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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 | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 1.0859 | 0.04 | 10 | 1.0722 | 0.6493 | 0.6735 | 0.6493 | 0.5118 |
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+ | 1.0731 | 0.07 | 20 | 1.0562 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 1.0456 | 0.11 | 30 | 1.0316 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 1.0199 | 0.15 | 40 | 0.9979 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.9613 | 0.19 | 50 | 0.9362 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.8949 | 0.22 | 60 | 0.8645 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.9151 | 0.26 | 70 | 0.8606 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.8583 | 0.3 | 80 | 0.8593 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.9604 | 0.33 | 90 | 0.8539 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.7919 | 0.37 | 100 | 0.8504 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.9365 | 0.41 | 110 | 0.8520 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.9285 | 0.45 | 120 | 0.8521 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.8564 | 0.48 | 130 | 0.8615 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.8132 | 0.52 | 140 | 0.8583 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.8911 | 0.56 | 150 | 0.8467 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.8383 | 0.59 | 160 | 0.8373 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.8387 | 0.63 | 170 | 0.8372 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.979 | 0.67 | 180 | 0.8595 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.7621 | 0.71 | 190 | 0.8642 | 0.6488 | 0.4209 | 0.6488 | 0.5105 |
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+ | 0.8367 | 0.74 | 200 | 0.8276 | 0.6553 | 0.6447 | 0.6553 | 0.5271 |
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+ | 0.9116 | 0.78 | 210 | 0.8466 | 0.6493 | 0.6735 | 0.6493 | 0.5118 |
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+ | 0.8444 | 0.82 | 220 | 0.8171 | 0.6504 | 0.6740 | 0.6504 | 0.5143 |
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+ | 0.7815 | 0.86 | 230 | 0.7919 | 0.6667 | 0.6008 | 0.6667 | 0.5615 |
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+ | 0.8592 | 0.89 | 240 | 0.7907 | 0.6732 | 0.5878 | 0.6732 | 0.5962 |
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+ | 0.8933 | 0.93 | 250 | 0.7963 | 0.6813 | 0.6004 | 0.6813 | 0.6102 |
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+ | 0.8409 | 0.97 | 260 | 0.7812 | 0.6797 | 0.6021 | 0.6797 | 0.6066 |
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+ | 0.8285 | 1.0 | 270 | 0.7794 | 0.6737 | 0.5987 | 0.6737 | 0.5940 |
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+ | 0.7895 | 1.04 | 280 | 0.7893 | 0.6846 | 0.6044 | 0.6846 | 0.6168 |
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+ | 0.8012 | 1.08 | 290 | 0.7617 | 0.6813 | 0.6129 | 0.6813 | 0.6002 |
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+ | 0.7215 | 1.12 | 300 | 0.8029 | 0.6748 | 0.6248 | 0.6748 | 0.5764 |
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+ | 0.8134 | 1.15 | 310 | 0.8294 | 0.6781 | 0.5949 | 0.6781 | 0.6294 |
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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+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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vocab.json ADDED
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