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mt5-small-task1-dataset2

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  1. README.md +20 -19
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@@ -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-task1-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: 0.5493
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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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@@ -41,25 +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: 8
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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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- | 3.4035 | 1.0 | 500 | 0.9806 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 1.049 | 2.0 | 1000 | 0.7479 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.8222 | 3.0 | 1500 | 0.6804 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.7272 | 4.0 | 2000 | 0.6246 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.6758 | 5.0 | 2500 | 0.5872 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.6367 | 6.0 | 3000 | 0.5728 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.6214 | 7.0 | 3500 | 0.5567 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.6107 | 8.0 | 4000 | 0.5493 | 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-task1-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: 0.3880
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+ - Accuracy: 0.182
 
 
 
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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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+ | 4.3254 | 1.0 | 250 | 0.7650 | 0.0 |
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+ | 0.9928 | 2.0 | 500 | 0.6343 | 0.034 |
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+ | 0.725 | 3.0 | 750 | 0.5447 | 0.114 |
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+ | 0.6197 | 4.0 | 1000 | 0.5004 | 0.106 |
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+ | 0.566 | 5.0 | 1250 | 0.4723 | 0.106 |
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+ | 0.5267 | 6.0 | 1500 | 0.4457 | 0.128 |
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+ | 0.4978 | 7.0 | 1750 | 0.4222 | 0.144 |
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+ | 0.4803 | 8.0 | 2000 | 0.4103 | 0.156 |
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+ | 0.4683 | 9.0 | 2250 | 0.3969 | 0.172 |
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+ | 0.4583 | 10.0 | 2500 | 0.3931 | 0.178 |
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+ | 0.4526 | 11.0 | 2750 | 0.3901 | 0.18 |
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+ | 0.4438 | 12.0 | 3000 | 0.3880 | 0.182 |
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  ### Framework versions