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--- |
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tags: |
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- summarization |
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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: exp2-led-risalah_data_v6 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/silmiaulia/huggingface/runs/7pt54hkh) |
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# exp2-led-risalah_data_v6 |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7971 |
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- Rouge1: 35.2105 |
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- Rouge2: 14.2825 |
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- Rougel: 18.7356 |
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- Rougelsum: 33.8518 |
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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: 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: linear |
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- lr_scheduler_warmup_steps: 200 |
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- num_epochs: 30 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 3.6579 | 1.0 | 20 | 2.9715 | 15.0902 | 2.4602 | 8.8016 | 14.54 | |
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| 3.8322 | 2.0 | 40 | 2.6400 | 19.8395 | 3.3421 | 10.0041 | 18.8629 | |
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| 3.3928 | 3.0 | 60 | 2.4780 | 24.1438 | 4.9177 | 11.8553 | 23.0439 | |
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| 3.1159 | 4.0 | 80 | 2.3336 | 26.1339 | 5.4015 | 12.1066 | 24.5407 | |
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| 2.8469 | 5.0 | 100 | 2.2554 | 25.3388 | 5.6665 | 12.0706 | 24.1799 | |
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| 2.6486 | 6.0 | 120 | 2.1842 | 33.8164 | 9.2363 | 15.7673 | 31.606 | |
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| 2.5429 | 7.0 | 140 | 2.1322 | 32.5361 | 8.5141 | 15.3201 | 30.935 | |
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| 2.3159 | 8.0 | 160 | 2.0631 | 32.3657 | 9.171 | 15.1179 | 30.9634 | |
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| 2.1821 | 10.0 | 200 | 1.9358 | 33.1626 | 10.8072 | 16.5887 | 31.0652 | |
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| 2.2141 | 11.0 | 220 | 1.9274 | 36.3525 | 13.5885 | 18.4941 | 34.9263 | |
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| 2.1213 | 12.0 | 240 | 1.9033 | 34.4359 | 11.4335 | 17.8322 | 32.5781 | |
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| 1.9791 | 13.0 | 260 | 1.8914 | 37.0733 | 14.2739 | 18.9338 | 35.5985 | |
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| 1.9504 | 14.0 | 280 | 1.8642 | 34.7529 | 13.0325 | 18.1055 | 33.257 | |
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| 1.9848 | 15.0 | 300 | 1.8641 | 35.9266 | 13.4528 | 18.459 | 34.0294 | |
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| 1.845 | 16.0 | 320 | 1.8507 | 37.7424 | 15.2488 | 18.993 | 35.4955 | |
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| 1.8049 | 17.0 | 340 | 1.8390 | 36.5023 | 13.6069 | 18.4956 | 34.883 | |
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| 1.8158 | 18.0 | 360 | 1.8393 | 34.4722 | 13.6438 | 18.1636 | 32.4511 | |
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| 1.8541 | 19.0 | 380 | 1.8395 | 37.0215 | 14.3221 | 19.6743 | 35.3083 | |
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| 1.7967 | 20.0 | 400 | 1.8403 | 36.3048 | 13.3475 | 19.9887 | 34.6884 | |
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| 1.7285 | 21.0 | 420 | 1.8394 | 36.4051 | 14.3198 | 19.4997 | 34.9803 | |
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| 1.7303 | 22.0 | 440 | 1.8287 | 36.1003 | 14.166 | 17.8619 | 34.3505 | |
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| 1.6976 | 23.0 | 460 | 1.8040 | 34.3036 | 12.8173 | 18.6643 | 32.6019 | |
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| 1.6916 | 24.0 | 480 | 1.7963 | 34.7753 | 14.0332 | 18.923 | 33.3743 | |
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| 1.6872 | 25.0 | 500 | 1.8073 | 37.0718 | 14.6821 | 20.1188 | 35.7824 | |
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| 1.6979 | 26.0 | 520 | 1.8340 | 37.1726 | 15.1384 | 20.2153 | 36.3188 | |
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| 1.6867 | 27.0 | 540 | 1.8000 | 37.2831 | 14.2806 | 19.1448 | 36.1598 | |
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| 1.6959 | 28.0 | 560 | 1.7886 | 34.8414 | 13.5902 | 18.5803 | 33.5383 | |
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| 1.7546 | 29.0 | 580 | 1.8068 | 37.6551 | 16.1055 | 20.2492 | 36.1177 | |
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| 1.632 | 30.0 | 600 | 1.7971 | 35.2105 | 14.2825 | 18.7356 | 33.8518 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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