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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: facebook/bart-large-cnn
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ - bleu
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+ model-index:
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+ - name: SocialScienceBARTPrincipal
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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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+ # SocialScienceBARTPrincipal
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+
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+ This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 4.8587
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+ - Rouge1: 48.4993
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+ - Rouge2: 14.8435
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+ - Rougel: 33.0264
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+ - Rougelsum: 44.9256
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+ - Bertscore Precision: 80.3517
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+ - Bertscore Recall: 82.7128
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+ - Bertscore F1: 81.5112
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+ - Bleu: 0.1092
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+ - Gen Len: 195.1640
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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: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 16
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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: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 | Bleu | Gen Len |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:|
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+ | 6.5089 | 0.1314 | 100 | 6.2390 | 39.4898 | 11.0769 | 27.6002 | 36.497 | 75.7798 | 80.6901 | 78.1466 | 0.0800 | 195.1640 |
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+ | 5.9338 | 0.2628 | 200 | 5.7540 | 41.6352 | 11.9524 | 29.0458 | 38.5778 | 77.0272 | 81.1993 | 79.0507 | 0.0882 | 195.1640 |
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+ | 5.6077 | 0.3943 | 300 | 5.4443 | 41.5238 | 12.2762 | 29.4389 | 38.8683 | 77.5496 | 81.3713 | 79.4075 | 0.0894 | 195.1640 |
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+ | 5.3997 | 0.5257 | 400 | 5.2541 | 44.1846 | 13.1247 | 30.5659 | 41.1211 | 78.8697 | 81.8978 | 80.3498 | 0.0962 | 195.1640 |
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+ | 5.1614 | 0.6571 | 500 | 5.1269 | 44.5045 | 13.3887 | 31.1505 | 41.1205 | 78.727 | 82.0655 | 80.3557 | 0.0994 | 195.1640 |
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+ | 5.0558 | 0.7885 | 600 | 4.9610 | 46.7823 | 14.4367 | 32.4159 | 43.2551 | 79.6807 | 82.5047 | 81.0632 | 0.1059 | 195.1640 |
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+ | 4.9749 | 0.9199 | 700 | 4.8587 | 48.4993 | 14.8435 | 33.0264 | 44.9256 | 80.3517 | 82.7128 | 81.5112 | 0.1092 | 195.1640 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
config.json ADDED
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+ }
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