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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: alexdg19/bert_large_xsum_samsum2
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - cnn_dailymail
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: bert_large_cnn_daily
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+ results:
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+ - task:
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+ name: Sequence-to-sequence Language Modeling
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+ type: text2text-generation
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+ dataset:
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+ name: cnn_dailymail
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+ type: cnn_dailymail
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+ config: 3.0.0
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+ split: test
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+ args: 3.0.0
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 0.4251
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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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+ # bert_large_cnn_daily
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+
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+ This model is a fine-tuned version of [alexdg19/bert_large_xsum_samsum2](https://huggingface.co/alexdg19/bert_large_xsum_samsum2) on the cnn_dailymail dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.7065
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+ - Rouge1: 0.4251
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+ - Rouge2: 0.2024
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+ - Rougel: 0.2992
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+ - Rougelsum: 0.3961
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+ - Gen Len: 60.6232
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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: 3
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+ - eval_batch_size: 3
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+ - seed: 42
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+ - gradient_accumulation_steps: 3
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+ - total_train_batch_size: 9
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | 1.6632 | 1.0 | 1021 | 1.6262 | 0.4191 | 0.1992 | 0.2957 | 0.39 | 60.6205 |
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+ | 1.3734 | 2.0 | 2042 | 1.6078 | 0.4253 | 0.2046 | 0.3009 | 0.397 | 61.0692 |
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+ | 1.1497 | 3.0 | 3064 | 1.6759 | 0.4254 | 0.2033 | 0.2998 | 0.3967 | 60.8555 |
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+ | 1.0123 | 4.0 | 4084 | 1.7065 | 0.4251 | 0.2024 | 0.2992 | 0.3961 | 60.6232 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ {
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+ "bos_token_id": 0,
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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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+ "forced_eos_token_id": 2,
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+ "max_length": 62,
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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": "4.35.0"
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+ }
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