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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: sshleifer/distilbart-cnn-12-6
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - dialogstudio
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: my_awesome_billsum_model
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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: dialogstudio
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+ type: dialogstudio
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+ config: TweetSumm
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+ split: test
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+ args: TweetSumm
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 0.4187
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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 [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the dialogstudio dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.9811
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+ - Rouge1: 0.4187
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+ - Rouge2: 0.1911
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+ - Rougel: 0.3373
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+ - Rougelsum: 0.338
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+ - Gen Len: 65.1636
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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: 16
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+ - eval_batch_size: 16
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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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+ - 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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+ | No log | 1.0 | 55 | 2.0591 | 0.4232 | 0.1899 | 0.3412 | 0.342 | 64.8545 |
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+ | No log | 2.0 | 110 | 1.9802 | 0.4125 | 0.19 | 0.3329 | 0.3334 | 66.7545 |
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+ | No log | 3.0 | 165 | 1.9671 | 0.4172 | 0.1927 | 0.3348 | 0.3357 | 65.3545 |
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+ | No log | 4.0 | 220 | 1.9811 | 0.4187 | 0.1911 | 0.3373 | 0.338 | 65.1636 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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