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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-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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+ model-index:
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+ - name: bart_samsum_finetuned_for_asr
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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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+ # bart_samsum_finetuned_for_asr
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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 the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.4623
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+ - Rouge1: 54.4349
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+ - Rouge2: 29.4619
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+ - Rougel: 44.7701
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+ - Rougelsum: 50.2825
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+ - Gen Len: 30.2751
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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: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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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: 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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+ | 1.3855 | 0.9997 | 1841 | 1.5274 | 52.3133 | 27.7547 | 43.0233 | 48.3891 | 30.3004 |
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+ | 1.0882 | 2.0 | 3683 | 1.4969 | 53.2457 | 28.4129 | 44.1196 | 49.1579 | 30.2637 |
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+ | 0.8376 | 2.9997 | 5524 | 1.5882 | 52.6929 | 27.5974 | 43.3339 | 47.9779 | 30.8034 |
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+ | 0.6756 | 4.0 | 7366 | 1.6617 | 52.5167 | 27.1278 | 43.037 | 48.1382 | 30.5299 |
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+ | 0.5417 | 4.9986 | 9205 | 1.8083 | 52.0696 | 26.8054 | 42.6108 | 47.5455 | 30.2894 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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