silmi224 commited on
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Training complete

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README.md ADDED
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+ ---
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+ base_model: silmi224/finetune-led-35000
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+ tags:
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+ - summarization
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+ - generated_from_trainer
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+ model-index:
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+ - name: led-risalah_data_v16
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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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+ # led-risalah_data_v16
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+
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+ This model is a fine-tuned version of [silmi224/finetune-led-35000](https://huggingface.co/silmi224/finetune-led-35000) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - eval_loss: 2.1156
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+ - eval_rouge1_precision: 0.6147
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+ - eval_rouge1_recall: 0.1563
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+ - eval_rouge1_fmeasure: 0.2489
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+ - eval_runtime: 105.7668
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+ - eval_samples_per_second: 0.095
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+ - eval_steps_per_second: 0.095
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+ - epoch: 26.35
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+ - step: 527
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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: 5.6e-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: 4
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+ - total_train_batch_size: 4
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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: 600
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+ - num_epochs: 30
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+ - mixed_precision_training: Native AMP
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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 2.1.2
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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+ "decoder_start_token_id": 2,
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+ "early_stopping": true,
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+ "eos_token_id": 2,
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+ "length_penalty": 2.0,
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+ "max_length": 128,
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+ "min_length": 40,
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+ "no_repeat_ngram_size": 3,
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+ "num_beams": 2,
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+ "pad_token_id": 1,
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+ "transformers_version": "4.41.2",
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+ "use_cache": false
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+ }
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