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rti-formatter

Transformers
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
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End of training

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  1. README.md +13 -8
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: nan
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  ## Model description
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@@ -35,23 +35,28 @@ 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: 8
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 4
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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 |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 15 | nan |
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- | No log | 2.0 | 30 | nan |
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- | No log | 3.0 | 45 | nan |
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- | No log | 4.0 | 60 | nan |
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8831
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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: 0.0003
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 9.9609 | 1.0 | 15 | 3.7048 |
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+ | 3.2663 | 2.0 | 30 | 2.4982 |
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+ | 2.5394 | 3.0 | 45 | 1.7657 |
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+ | 1.6881 | 4.0 | 60 | 1.2883 |
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+ | 1.4200 | 5.0 | 75 | 1.0623 |
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+ | 1.1158 | 6.0 | 90 | 0.9751 |
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+ | 1.0128 | 7.0 | 105 | 0.9256 |
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+ | 0.9078 | 8.0 | 120 | 0.8989 |
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+ | 0.9097 | 9.0 | 135 | 0.8891 |
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+ | 0.8413 | 10.0 | 150 | 0.8831 |
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  ### Framework versions