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t5-base-finetuned-xsum

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 +12 -13
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,12 +18,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.8388
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- - Rouge1: 12.5
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- - Rouge2: 0.0
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- - Rougel: 12.5
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- - Rougelsum: 12.5
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- - Gen Len: 20.0
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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- - train_batch_size: 4
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- - eval_batch_size: 4
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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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  - lr_scheduler_warmup_ratio: 0.05
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  - num_epochs: 2
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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 | 1 | 2.8388 | 12.5 | 0.0 | 12.5 | 12.5 | 20.0 |
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- | No log | 2.0 | 2 | 2.8388 | 12.5 | 0.0 | 12.5 | 12.5 | 20.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.8406
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+ - Rouge1: 19.6794
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+ - Rouge2: 3.8793
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+ - Rougel: 16.712
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+ - Rougelsum: 16.6918
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+ - Gen Len: 19.6
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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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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  - lr_scheduler_warmup_ratio: 0.05
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  - num_epochs: 2
 
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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 | 10 | 2.9172 | 19.3896 | 3.8268 | 17.1724 | 17.058 | 19.6 |
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+ | No log | 2.0 | 20 | 2.8406 | 19.6794 | 3.8793 | 16.712 | 16.6918 | 19.6 |
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  ### Framework versions
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