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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: allenai/led-base-16384
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: my_awesome_billsum_model
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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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+ # my_awesome_billsum_model
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+
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+ This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - eval_loss: 1.7927
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+ - eval_rouge1: 0.1895
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+ - eval_rouge2: 0.0969
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+ - eval_rougeL: 0.1641
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+ - eval_rougeLsum: 0.1692
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+ - eval_gen_len: 20.0
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+ - eval_runtime: 47.5253
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+ - eval_samples_per_second: 5.218
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+ - eval_steps_per_second: 1.052
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+ - epoch: 2.0
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+ - step: 396
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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: 5
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+ - eval_batch_size: 5
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+ - seed: 42
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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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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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+ {
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+ "_name_or_path": "allenai/led-base-16384",
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+ "activation_dropout": 0.0,
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+ "activation_function": "gelu",
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+ "architectures": [
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+ "LEDForConditionalGeneration"
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+ ],
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+ "model_type": "led",
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+ "num_hidden_layers": 6,
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