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tmp_test

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End of training

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Files changed (8) hide show
  1. README.md +29 -4
  2. config.json +1 -1
  3. generation_config.json +0 -1
  4. model.safetensors +1 -1
  5. runs/Feb24_20-12-06_94086e04c5b2/events.out.tfevents.1740427929.94086e04c5b2.318.1 +3 -0
  6. runs/Feb24_20-12-06_94086e04c5b2/events.out.tfevents.1740428950.94086e04c5b2.318.2 +3 -0
  7. runs/Feb24_20-57-52_94086e04c5b2/events.out.tfevents.1740430677.94086e04c5b2.32775.0 +3 -0
  8. training_args.bin +2 -2
README.md CHANGED
@@ -1,9 +1,11 @@
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  ---
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  library_name: transformers
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  license: apache-2.0
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- base_model: google-t5/t5-small
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: tmp_test
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  results: []
@@ -14,7 +16,14 @@ should probably proofread and complete it, then remove this comment. -->
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  # tmp_test
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- This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
 
 
 
 
 
 
 
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  ## Model description
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@@ -33,20 +42,36 @@ More information needed
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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: 16
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  - eval_batch_size: 16
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  - seed: 42
 
 
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 2
 
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  ### Training results
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  ### Framework versions
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  - Transformers 4.48.3
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  - Pytorch 2.5.1+cu124
 
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  - Tokenizers 0.21.0
 
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  ---
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  library_name: transformers
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  license: apache-2.0
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+ base_model: t5-small
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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: tmp_test
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  results: []
 
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  # tmp_test
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+ This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.4968
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+ - Rouge1: 0.1438
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+ - Rouge2: 0.0337
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+ - Rougel: 0.1049
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+ - Rougelsum: 0.1052
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+ - Gen Len: 20.0
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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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 | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 25 | 4.3210 | 0.1303 | 0.0263 | 0.0973 | 0.0974 | 20.0 |
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+ | No log | 2.0 | 50 | 3.8167 | 0.1344 | 0.0288 | 0.1005 | 0.1005 | 20.0 |
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+ | No log | 3.0 | 75 | 3.6506 | 0.1386 | 0.0305 | 0.1023 | 0.1024 | 20.0 |
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+ | No log | 4.0 | 100 | 3.5756 | 0.1426 | 0.0317 | 0.1044 | 0.1045 | 20.0 |
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+ | No log | 5.0 | 125 | 3.5415 | 0.1433 | 0.0323 | 0.1044 | 0.1045 | 20.0 |
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+ | No log | 6.0 | 150 | 3.5215 | 0.1425 | 0.0321 | 0.1039 | 0.104 | 20.0 |
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+ | No log | 7.0 | 175 | 3.5101 | 0.1436 | 0.0325 | 0.1047 | 0.1048 | 20.0 |
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+ | 3.9618 | 8.0 | 200 | 3.5025 | 0.1435 | 0.0331 | 0.105 | 0.1051 | 20.0 |
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+ | 3.9618 | 9.0 | 225 | 3.4982 | 0.1438 | 0.0337 | 0.1049 | 0.1052 | 20.0 |
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+ | 3.9618 | 10.0 | 250 | 3.4968 | 0.1438 | 0.0337 | 0.1049 | 0.1052 | 20.0 |
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  ### Framework versions
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  - Transformers 4.48.3
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  - Pytorch 2.5.1+cu124
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+ - Datasets 3.3.2
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  - Tokenizers 0.21.0
config.json CHANGED
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  "T5ForConditionalGeneration"
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