End of training
Browse files- README.md +22 -7
- all_results.json +29 -0
- eval_results.json +13 -0
- generated_predictions.txt +0 -0
- predict_results.json +12 -0
- train_results.json +9 -0
- trainer_state.json +130 -0
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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- rouge
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model-index:
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- name: liputan6-seq_bn-rf16
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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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# liputan6-seq_bn-rf16
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.7479
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- Rouge1:
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- Rouge2:
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- Rougel:
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- Rougelsum:
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- Gen Len:
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## Model description
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---
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language:
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- id
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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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- rouge
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model-index:
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- name: liputan6-seq_bn-rf16
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results:
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- task:
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name: Summarization
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type: summarization
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dataset:
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name: id_liputan6 canonical
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type: id_liputan6
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config: canonical
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split: validation
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args: canonical
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metrics:
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- name: Rouge1
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type: rouge
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value: 27.6391
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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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# liputan6-seq_bn-rf16
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 canonical dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.7479
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- Rouge1: 27.6391
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- Rouge2: 12.5407
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- Rougel: 23.5774
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- Rougelsum: 25.3376
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- Gen Len: 39.933
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## Model description
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all_results.json
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{
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"epoch": 5.0,
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"eval_gen_len": 39.933,
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"eval_loss": 2.7479429244995117,
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"eval_rouge1": 27.6391,
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"eval_rouge2": 12.5407,
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"eval_rougeL": 23.5774,
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"eval_rougeLsum": 25.3376,
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"eval_runtime": 579.6294,
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"eval_samples": 1000,
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"eval_samples_per_second": 1.725,
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"eval_steps_per_second": 0.055,
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"predict_gen_len": 38.109,
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"predict_loss": 2.1557793617248535,
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"predict_rouge1": 35.0494,
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"predict_rouge2": 18.8325,
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"predict_rougeL": 30.2344,
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"predict_rougeLsum": 32.847,
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"predict_runtime": 569.6774,
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"predict_samples": 1000,
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"predict_samples_per_second": 1.755,
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"predict_steps_per_second": 0.056,
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"total_flos": 3451266662400000.0,
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"train_loss": 2.1248473152281746,
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"train_runtime": 753.9081,
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"train_samples": 1000,
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"train_samples_per_second": 6.632,
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"train_steps_per_second": 0.418
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}
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eval_results.json
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{
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"epoch": 5.0,
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"eval_gen_len": 39.933,
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"eval_loss": 2.7479429244995117,
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"eval_rouge1": 27.6391,
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"eval_rouge2": 12.5407,
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"eval_rougeL": 23.5774,
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"eval_rougeLsum": 25.3376,
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"eval_runtime": 579.6294,
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"eval_samples": 1000,
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"eval_samples_per_second": 1.725,
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"eval_steps_per_second": 0.055
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}
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generated_predictions.txt
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predict_results.json
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{
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"predict_gen_len": 38.109,
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"predict_loss": 2.1557793617248535,
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"predict_rouge1": 35.0494,
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"predict_rouge2": 18.8325,
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"predict_rougeL": 30.2344,
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"predict_rougeLsum": 32.847,
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"predict_runtime": 569.6774,
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"predict_samples": 1000,
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"predict_samples_per_second": 1.755,
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"predict_steps_per_second": 0.056
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}
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train_results.json
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{
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"epoch": 5.0,
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"total_flos": 3451266662400000.0,
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"train_loss": 2.1248473152281746,
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"train_runtime": 753.9081,
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"train_samples": 1000,
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"train_samples_per_second": 6.632,
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"train_steps_per_second": 0.418
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}
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trainer_state.json
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