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End of training

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README.md ADDED
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+ ---
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+ base_model: ingeniumacademy/bart-cnn-samsum-finetuned
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+ datasets:
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+ - samsum
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+ library_name: peft
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: bart-cnn-samsum-peft
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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-cnn-samsum-peft
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+
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+ This model is a fine-tuned version of [ingeniumacademy/bart-cnn-samsum-finetuned](https://huggingface.co/ingeniumacademy/bart-cnn-samsum-finetuned) on the samsum dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1345
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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: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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: 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 |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.078 | 1.0 | 19 | 0.1345 |
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+ | 0.0865 | 2.0 | 38 | 0.1345 |
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+ | 0.0768 | 3.0 | 57 | 0.1345 |
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+ | 0.079 | 4.0 | 76 | 0.1345 |
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+ | 0.0916 | 5.0 | 95 | 0.1345 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ "init_lora_weights": true,
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+ "loftq_config": {},
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+ "peft_type": "LORA",
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+ "r": 32,
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+ "target_modules": [
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+ "q_proj",
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+ "v_proj"
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+ ],
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+ "task_type": "SEQ_2_SEQ_LM",
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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