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tvganesh
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test_trainer1

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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test_trainer1 / README.md
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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: test_trainer1
    results: []

test_trainer1

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0000
  • Rouge1: 0.8111
  • Rouge2: 0.8008
  • Rougel: 0.812
  • Rougelsum: 0.8109
  • Gen Len: 18.5

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0056
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-06
  • lr_scheduler_type: linear
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 13 0.3042 0.7518 0.7064 0.7515 0.7499 18.2
No log 2.0 26 0.0621 0.7853 0.7648 0.7778 0.778 18.4667
No log 3.0 39 0.0600 0.7809 0.7539 0.7793 0.7794 18.3333
No log 4.0 52 0.0293 0.8073 0.7961 0.8076 0.8069 18.4
No log 5.0 65 0.0304 0.8053 0.7881 0.803 0.8027 18.4667
No log 6.0 78 0.0167 0.7787 0.7634 0.7794 0.7792 18.7
No log 7.0 91 0.0203 0.8076 0.7952 0.8083 0.8072 18.5333
No log 8.0 104 0.0418 0.7722 0.7493 0.7711 0.7695 18.7667
No log 9.0 117 0.0153 0.799 0.7804 0.7969 0.7964 18.4
No log 10.0 130 0.0225 0.7963 0.7804 0.7968 0.7952 18.5
No log 11.0 143 0.0119 0.7832 0.7676 0.784 0.7837 18.5
No log 12.0 156 0.0118 0.8023 0.7863 0.8024 0.8011 18.5
No log 13.0 169 0.0411 0.8019 0.7916 0.8034 0.8025 18.2667
No log 14.0 182 0.0048 0.8017 0.791 0.8029 0.8022 18.5
No log 15.0 195 0.0038 0.8111 0.8008 0.812 0.8109 18.5
No log 16.0 208 0.0080 0.8091 0.7967 0.8093 0.8086 18.5
No log 17.0 221 0.0046 0.8092 0.7967 0.8103 0.8095 18.5
No log 18.0 234 0.0023 0.8111 0.8008 0.812 0.8109 18.5
No log 19.0 247 0.0097 0.8105 0.799 0.8116 0.8105 18.5
No log 20.0 260 0.0024 0.8111 0.8008 0.812 0.8109 18.5
No log 21.0 273 0.0018 0.8111 0.7995 0.812 0.8109 18.5
No log 22.0 286 0.0030 0.8111 0.8008 0.812 0.8109 18.5
No log 23.0 299 0.0042 0.8111 0.8008 0.812 0.8109 18.5
No log 24.0 312 0.0065 0.8102 0.8 0.8114 0.8099 18.5
No log 25.0 325 0.0004 0.8111 0.8008 0.812 0.8109 18.5
No log 26.0 338 0.0001 0.8111 0.8008 0.812 0.8109 18.5
No log 27.0 351 0.0001 0.8111 0.8008 0.812 0.8109 18.5
No log 28.0 364 0.0010 0.8111 0.8008 0.812 0.8109 18.5
No log 29.0 377 0.0002 0.8111 0.8008 0.812 0.8109 18.5
No log 30.0 390 0.0001 0.8111 0.8008 0.812 0.8109 18.5
No log 31.0 403 0.0020 0.8093 0.7975 0.8103 0.8089 18.5
No log 32.0 416 0.0014 0.8093 0.7975 0.8103 0.8089 18.5
No log 33.0 429 0.0001 0.8111 0.8008 0.812 0.8109 18.5
No log 34.0 442 0.0000 0.8111 0.8008 0.812 0.8109 18.5
No log 35.0 455 0.0000 0.8111 0.8008 0.812 0.8109 18.5
No log 36.0 468 0.0000 0.8111 0.8008 0.812 0.8109 18.5
No log 37.0 481 0.0000 0.8111 0.8008 0.812 0.8109 18.5
No log 38.0 494 0.0000 0.8111 0.8008 0.812 0.8109 18.5
0.068 39.0 507 0.0000 0.8111 0.8008 0.812 0.8109 18.5
0.068 40.0 520 0.0000 0.8111 0.8008 0.812 0.8109 18.5

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.0
  • Datasets 2.14.5
  • Tokenizers 0.13.3