Model save
Browse files- README.md +57 -0
- generation_config.json +13 -0
- pytorch_model.bin +1 -1
README.md
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---
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license: apache-2.0
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base_model: facebook/bart-large
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tags:
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- generated_from_trainer
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model-index:
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- name: bart-large-retry-finetune-indosum
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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-large-retry-finetune-indosum
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This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3273
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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: 2e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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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: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 0.3437 | 1.0 | 35677 | 0.3273 |
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### Framework versions
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- Transformers 4.32.1
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- Pytorch 2.0.0
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- Datasets 2.12.0
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- Tokenizers 0.13.2
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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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"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": "4.32.1"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 1625541389
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version https://git-lfs.github.com/spec/v1
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oid sha256:2cb9ad8098f4924ac700b484fd7852e585a4a8cd7cf8ee4bb97efac2effc5212
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size 1625541389
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