Model save
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README.md
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---
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license: apache-2.0
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base_model: LazarusNLP/IndoNanoT5-base
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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: summarization-lora-2
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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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# summarization-lora-2
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5532
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- Rouge1: 0.3696
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- Rouge2: 0.0
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- Rougel: 0.3694
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- Rougelsum: 0.3713
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- Gen Len: 1.0
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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: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 32
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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: 5.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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| 1.3998 | 1.0 | 1787 | 0.6384 | 0.3848 | 0.0 | 0.3845 | 0.3857 | 1.0 |
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| 0.8601 | 2.0 | 3574 | 0.5793 | 0.391 | 0.0 | 0.391 | 0.3923 | 1.0 |
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| 0.7972 | 3.0 | 5361 | 0.5576 | 0.3776 | 0.0 | 0.3767 | 0.3768 | 1.0 |
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| 0.7698 | 4.0 | 7148 | 0.5620 | 0.3579 | 0.0 | 0.3565 | 0.3592 | 1.0 |
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| 0.7566 | 5.0 | 8935 | 0.5532 | 0.3696 | 0.0 | 0.3694 | 0.3713 | 1.0 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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adapter-summarization/adapter_config.json
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{
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"config": {
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"alpha": 8,
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"architecture": "lora",
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"attn_matrices": [
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"q",
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"v"
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],
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"composition_mode": "add",
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"dropout": 0.0,
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"init_weights": "lora",
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"intermediate_lora": false,
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"leave_out": [],
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"output_lora": false,
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"r": 8,
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"selfattn_lora": true,
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"use_gating": false
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},
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"config_id": "625403edad0bf919",
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"hidden_size": 768,
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"model_class": "T5ForConditionalGeneration",
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"model_name": "LazarusNLP/IndoNanoT5-base",
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"model_type": "t5",
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"name": "adapter-summarization",
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"version": "0.2.2"
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}
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adapter-summarization/head_config.json
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{
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"config": null,
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"hidden_size": 768,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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"model_class": "T5ForConditionalGeneration",
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"model_name": "LazarusNLP/IndoNanoT5-base",
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"model_type": "t5",
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"name": null,
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"num_labels": 2,
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"version": "0.2.2"
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}
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adapter-summarization/pytorch_adapter.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:290b0fb5c10431e545ad416905763858fe985187864f8dfb010b4bf3ac12e404
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size 3593010
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adapter-summarization/pytorch_model_head.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7467a987e0db5b7ef33f0dba6f30173b6f2a0fa4327e8d394e655fc96809b7cf
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size 98698515
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