hassaanshafqat
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Browse files- README.md +62 -0
- generation_config.json +13 -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: facebook/bart-base
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tags:
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- generated_from_trainer
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datasets:
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- xsum
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model-index:
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- name: bart-xsum
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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-xsum
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the xsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1135
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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: 4
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- eval_batch_size: 4
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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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.1699 | 1.0 | 250 | 0.1267 |
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| 0.1294 | 2.0 | 500 | 0.1141 |
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| 0.1187 | 3.0 | 750 | 0.1135 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.19.1
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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": "4.44.2"
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}
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