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mt5-small-task2-dataset2

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End of training

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  1. README.md +20 -17
README.md CHANGED
@@ -4,7 +4,7 @@ base_model: google/mt5-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: mt5-small-task2-dataset2
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  results: []
@@ -17,11 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5765
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- - Rouge1: 0.0
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- - Rouge2: 0.0
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- - Rougel: 0.0
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- - Rougelsum: 0.0
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  ## Model description
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@@ -41,23 +38,29 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5.6e-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: 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: 6
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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- | 3.9862 | 1.0 | 500 | 1.0412 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 1.3633 | 2.0 | 1000 | 0.7485 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.9873 | 3.0 | 1500 | 0.6652 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.8529 | 4.0 | 2000 | 0.6117 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.7724 | 5.0 | 2500 | 0.5854 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.7457 | 6.0 | 3000 | 0.5765 | 0.0 | 0.0 | 0.0 | 0.0 |
 
 
 
 
 
 
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  ### Framework versions
 
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  tags:
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  - generated_from_trainer
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  metrics:
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+ - accuracy
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  model-index:
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  - name: mt5-small-task2-dataset2
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  results: []
 
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  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4228
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+ - Accuracy: 0.32
 
 
 
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5.6e-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: 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: 12
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 6.2681 | 1.0 | 250 | 1.1622 | 0.018 |
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+ | 1.7716 | 2.0 | 500 | 0.8039 | 0.066 |
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+ | 1.1424 | 3.0 | 750 | 0.6418 | 0.14 |
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+ | 0.8879 | 4.0 | 1000 | 0.5569 | 0.204 |
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+ | 0.7728 | 5.0 | 1250 | 0.5065 | 0.256 |
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+ | 0.6886 | 6.0 | 1500 | 0.4821 | 0.268 |
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+ | 0.6422 | 7.0 | 1750 | 0.4619 | 0.282 |
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+ | 0.6137 | 8.0 | 2000 | 0.4500 | 0.298 |
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+ | 0.5837 | 9.0 | 2250 | 0.4314 | 0.3 |
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+ | 0.5711 | 10.0 | 2500 | 0.4256 | 0.316 |
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+ | 0.5596 | 11.0 | 2750 | 0.4228 | 0.316 |
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+ | 0.5458 | 12.0 | 3000 | 0.4228 | 0.32 |
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  ### Framework versions