Finetuned on QA dataset
Browse files- README.md +55 -0
- generation_config.json +6 -2
README.md
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---
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library_name: transformers
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license: cc-by-sa-4.0
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base_model: ku-nlp/bart-base-japanese
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tags:
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- generated_from_trainer
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model-index:
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- name: bart_finetuned
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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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# bart_finetuned
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This model is a fine-tuned version of [ku-nlp/bart-base-japanese](https://huggingface.co/ku-nlp/bart-base-japanese) on an unknown dataset.
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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: 5e-05
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 10
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.52.3
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- Pytorch 2.7.0+cu118
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- Tokenizers 0.21.1
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generation_config.json
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{
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-
"
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"early_stopping": true,
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"
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"no_repeat_ngram_size": 3,
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"num_beams": 4,
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"transformers_version": "4.52.3"
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}
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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_eos_token_id": 2,
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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": "4.52.3"
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}
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