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End of training

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README.md CHANGED
@@ -3,6 +3,8 @@ 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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  model-index:
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  - name: Summary
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  results: []
@@ -14,6 +16,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # Summary
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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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  ## Model description
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@@ -38,14 +47,18 @@ The following hyperparameters were used during training:
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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: 1
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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 | 282 | 1.8062 | 0.2428 | 0.1162 | 0.2011 | 0.2011 | 18.9976 |
 
 
 
 
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  ### Framework versions
 
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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: Summary
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  results: []
 
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  # Summary
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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: 1.7430
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+ - Rouge1: 0.2448
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+ - Rouge2: 0.1173
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+ - Rougel: 0.2028
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+ - Rougelsum: 0.2029
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+ - Gen Len: 19.0
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  ## Model description
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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: 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 282 | 1.7743 | 0.2429 | 0.1151 | 0.2007 | 0.2008 | 18.9976 |
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+ | 2.0101 | 2.0 | 564 | 1.7550 | 0.2448 | 0.1169 | 0.203 | 0.2032 | 18.9976 |
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+ | 2.0101 | 3.0 | 846 | 1.7477 | 0.2451 | 0.1178 | 0.2034 | 0.2036 | 18.9976 |
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+ | 1.9145 | 4.0 | 1128 | 1.7441 | 0.2449 | 0.1173 | 0.2028 | 0.203 | 18.9976 |
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+ | 1.9145 | 5.0 | 1410 | 1.7430 | 0.2448 | 0.1173 | 0.2028 | 0.2029 | 19.0 |
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  ### Framework versions
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