ubaada/pegasus-x-large-booksum-16k
Browse files- README.md +17 -40
- config.json +1 -1
- model.safetensors +1 -1
- tokenizer.json +4 -2
- tokenizer_config.json +8 -1
- training_args.bin +2 -2
README.md
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---
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base_model:
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tags:
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- summary
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- booksum
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- long-document
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- long-form
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datasets:
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- ubaada/booksum-complete-cleaned
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language:
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- en
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pipeline_tag: summarization
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metrics:
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model-index:
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- task:
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type: summarization
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name: Summarization
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dataset:
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name: BookSum
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type: ubaada/booksum-complete-cleaned
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config: ubaada--booksum
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split: test
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metrics:
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- type: rouge
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value: 30.947853
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name: ROUGE-1
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verified: false
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- type: rouge
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value: 5.568146
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name: ROUGE-2
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verified: false
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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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# pegasus-x-large-booksum-16k
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Rouge1: 0.
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- Rouge2: 0.
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- Rougel: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 8
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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:
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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: 1
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|
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| 1.
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.2.0
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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---
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base_model: ubaada/pegasus-x-large-booksum-16k
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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: pegasus-x-large-booksum-16k
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results: []
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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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# pegasus-x-large-booksum-16k
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This model is a fine-tuned version of [ubaada/pegasus-x-large-booksum-16k](https://huggingface.co/ubaada/pegasus-x-large-booksum-16k) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.9879
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- Rouge1: 0.2983
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- Rouge2: 0.0463
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- Rougel: 0.1367
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 4e-05
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- train_batch_size: 8
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- total_eval_batch_size: 2
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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: 1
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|
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| 1.3846 | 0.9992 | 314 | 1.9879 | 0.2983 | 0.0463 | 0.1367 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.2.0
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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config.json
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"activation_dropout": 0.1,
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"activation_function": "relu",
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"add_bias_logits": false,
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"activation_dropout": 0.1,
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"activation_function": "relu",
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model.safetensors
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tokenizer.json
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tokenizer_config.json
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training_args.bin
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