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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-xsum
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: LLM_Teached_Bart_50k
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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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+ # LLM_Teached_Bart_50k
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+
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+ This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.5590
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+ - Rouge1: 0.4909
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+ - Rouge2: 0.2303
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+ - Rougel: 0.3967
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+ - Rougelsum: 0.3965
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+ - Gen Len: 38.2287
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+ - Precision: 0.9063
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+ - Recall: 0.9187
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+ - F1: 0.9123
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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: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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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+ - num_epochs: 4
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 390 | 1.6214 | 0.4804 | 0.2218 | 0.3873 | 0.3873 | 38.3549 | 0.9049 | 0.9166 | 0.9106 |
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+ | 1.5842 | 2.0 | 781 | 1.5548 | 0.4874 | 0.2283 | 0.3945 | 0.3945 | 37.8604 | 0.9059 | 0.9171 | 0.9113 |
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+ | 1.3014 | 3.0 | 1172 | 1.5461 | 0.49 | 0.2294 | 0.3975 | 0.3974 | 37.7564 | 0.9064 | 0.918 | 0.912 |
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+ | 1.18 | 3.99 | 1560 | 1.5590 | 0.4909 | 0.2303 | 0.3967 | 0.3965 | 38.2287 | 0.9063 | 0.9187 | 0.9123 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.5
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+ - Tokenizers 0.15.0
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+ "early_stopping": true,
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+ "min_length": 11,
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+ "no_repeat_ngram_size": 3,
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+ "num_beams": 6,
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+ "pad_token_id": 1,
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+ "transformers_version": "4.36.0"
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+ }
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