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flan-log-sage

Text2Text Generation
Transformers
TensorBoard
Safetensors
t5
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
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  1. README.md +179 -0
  2. generation_config.json +6 -0
  3. runs/Jun24_19-32-06_b17a6d158ec2/events.out.tfevents.1719257528.b17a6d158ec2.3400.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/flan-t5-base
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - hdfs_log_summary_dataset
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: flan-log-sage
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+ results:
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+ - task:
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+ name: Sequence-to-sequence Language Modeling
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+ type: text2text-generation
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+ dataset:
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+ name: hdfs_log_summary_dataset
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+ type: hdfs_log_summary_dataset
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 0.0737
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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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+ # flan-log-sage
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+
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+ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the hdfs_log_summary_dataset dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: nan
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+ - Rouge1: 0.0737
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+ - Rouge2: 0.0154
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+ - Rougel: 0.0737
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+ - Rougelsum: 0.0741
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+ - Gen Len: 19.0
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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: 2e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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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: 100
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+ - mixed_precision_training: Native AMP
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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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+ | No log | 1.0 | 23 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 2.0 | 46 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 3.0 | 69 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 4.0 | 92 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 5.0 | 115 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 6.0 | 138 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 7.0 | 161 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 8.0 | 184 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 9.0 | 207 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 10.0 | 230 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 11.0 | 253 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 12.0 | 276 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 13.0 | 299 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 14.0 | 322 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 15.0 | 345 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 16.0 | 368 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 17.0 | 391 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 18.0 | 414 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 19.0 | 437 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 20.0 | 460 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | No log | 21.0 | 483 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 22.0 | 506 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 23.0 | 529 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 24.0 | 552 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 25.0 | 575 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 26.0 | 598 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 27.0 | 621 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 28.0 | 644 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 29.0 | 667 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 30.0 | 690 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 31.0 | 713 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 32.0 | 736 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 33.0 | 759 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 34.0 | 782 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 35.0 | 805 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 36.0 | 828 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 37.0 | 851 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 38.0 | 874 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 39.0 | 897 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 40.0 | 920 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 41.0 | 943 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 42.0 | 966 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 43.0 | 989 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 44.0 | 1012 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 45.0 | 1035 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 46.0 | 1058 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 47.0 | 1081 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 48.0 | 1104 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 49.0 | 1127 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 50.0 | 1150 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 51.0 | 1173 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 52.0 | 1196 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 57.0 | 1311 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 59.0 | 1357 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 60.0 | 1380 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 61.0 | 1403 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 62.0 | 1426 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 63.0 | 1449 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 68.0 | 1564 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 69.0 | 1587 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 70.0 | 1610 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 71.0 | 1633 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 80.0 | 1840 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 81.0 | 1863 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 82.0 | 1886 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 83.0 | 1909 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 85.0 | 1955 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 86.0 | 1978 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 93.0 | 2139 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 94.0 | 2162 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 95.0 | 2185 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 96.0 | 2208 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 97.0 | 2231 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 98.0 | 2254 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 99.0 | 2277 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+ | 0.0 | 100.0 | 2300 | nan | 0.0737 | 0.0154 | 0.0737 | 0.0741 | 19.0 |
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+
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+
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+ ### Framework versions
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+
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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
generation_config.json ADDED
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+ {
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+ "decoder_start_token_id": 0,
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+ "eos_token_id": 1,
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+ "pad_token_id": 0,
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+ "transformers_version": "4.41.2"
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+ }
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