Model save
Browse files- README.md +66 -0
- generation_config.json +16 -0
README.md
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---
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library_name: transformers
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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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model-index:
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- name: distilbart-summarization-top
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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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should probably proofread and complete it, then remove this comment. -->
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# distilbart-summarization-top
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0451
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-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: Use OptimizerNames.ADAFACTOR and the args are:
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No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 2.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:-----:|:---------------:|
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| 1.1609 | 0.3765 | 2000 | 1.0716 |
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| 1.155 | 0.7529 | 4000 | 1.0546 |
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| 1.0795 | 1.1293 | 6000 | 1.0495 |
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| 1.0429 | 1.5058 | 8000 | 1.0466 |
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| 1.0584 | 1.8823 | 10000 | 1.0451 |
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### Framework versions
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- Transformers 4.48.2
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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generation_config.json
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{
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"_from_model_config": true,
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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_bos_token_id": 0,
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"forced_eos_token_id": 2,
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"length_penalty": 2.0,
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"max_length": 142,
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"min_length": 56,
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"no_repeat_ngram_size": 3,
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"num_beams": 4,
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"pad_token_id": 1,
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"transformers_version": "4.48.2"
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}
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