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End of training

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  2. adapter_model.safetensors +1 -1
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ base_model: google/long-t5-tglobal-xl
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: LongT5-XLarge-NSPCC
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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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+ # LongT5-XLarge-NSPCC
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+
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+ This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6843
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+ - Rouge1: 0.5138
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+ - Rouge2: 0.2297
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+ - Rougel: 0.2999
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+ - Rougelsum: 0.2995
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+ - Gen Len: 337.6809
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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: 0.0003
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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: 4
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+ - total_train_batch_size: 4
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.03
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+ - num_epochs: 4
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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 | Gen Len |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
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+ | 3.6911 | 0.9960 | 188 | 0.7292 | 0.4665 | 0.1826 | 0.2611 | 0.2611 | 360.7021 |
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+ | 0.8701 | 1.9974 | 377 | 0.6967 | 0.4886 | 0.2073 | 0.2805 | 0.2799 | 365.3298 |
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+ | 0.7849 | 2.9987 | 566 | 0.6808 | 0.5116 | 0.2302 | 0.2995 | 0.2997 | 332.3191 |
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+ | 0.7769 | 3.9841 | 752 | 0.6843 | 0.5138 | 0.2297 | 0.2999 | 0.2995 | 337.6809 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.10.0
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+ - Transformers 4.40.1
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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