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ShushantLLM/bartHW3LLM

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: facebook/bart-large-xsum
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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: bart-large-xsum-finetuned-sst2
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+ results: []
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+ ---
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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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+
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+ # bart-large-xsum-finetuned-sst2
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+
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+ This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4333
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+ - Rouge1: 0.5389
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+ - Rouge2: 0.2841
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+ - Rougel: 0.4406
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+ - Rougelsum: 0.4935
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 16
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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: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | 0.3028 | 1.0 | 920 | 0.3135 | 0.5331 | 0.2844 | 0.4417 | 0.4908 |
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+ | 0.2301 | 2.0 | 1841 | 0.3304 | 0.5371 | 0.2878 | 0.4393 | 0.4936 |
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+ | 0.1626 | 3.0 | 2762 | 0.3395 | 0.5415 | 0.2907 | 0.4503 | 0.4978 |
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+ | 0.112 | 4.0 | 3683 | 0.3898 | 0.5415 | 0.2830 | 0.4406 | 0.4952 |
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+ | 0.0747 | 5.0 | 4600 | 0.4333 | 0.5389 | 0.2841 | 0.4406 | 0.4935 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
config.json ADDED
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+ {
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+ "_name_or_path": "facebook/bart-large-xsum",
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+ "activation_function": "gelu",
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+ "architectures": [
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+ "BartForConditionalGeneration"
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+ ],
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+ "vocab_size": 50264
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+ }
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