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DanSarm
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receipt-core-model

Transformers
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
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Training complete!

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  1. README.md +15 -11
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
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 [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2148
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  ## Model description
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@@ -35,24 +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: 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 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: 5
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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 | 2.0706 |
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- | No log | 2.0 | 30 | 1.3772 |
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- | No log | 3.0 | 45 | 1.2762 |
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- | No log | 4.0 | 60 | 1.2304 |
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- | No log | 5.0 | 75 | 1.2148 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4566
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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: 0.0005
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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 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: 100
 
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 5.6391 | 1.0 | 8 | 1.9149 |
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+ | 1.1508 | 2.0 | 16 | 1.4115 |
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+ | 0.5832 | 3.0 | 24 | 1.3418 |
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+ | 0.3521 | 4.0 | 32 | 1.3398 |
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+ | 0.262 | 5.0 | 40 | 1.3215 |
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+ | 0.2127 | 6.0 | 48 | 1.3763 |
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+ | 0.1671 | 7.0 | 56 | 1.4019 |
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+ | 0.1425 | 8.0 | 64 | 1.4218 |
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+ | 0.1332 | 9.0 | 72 | 1.4471 |
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+ | 0.1183 | 10.0 | 80 | 1.4566 |
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  ### Framework versions
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