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mt5-small-task2-dataset4

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  1. README.md +21 -18
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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-task2-dataset4
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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: 0.5672
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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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@@ -41,28 +38,34 @@ 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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- | 0.438 | 1.0 | 500 | 0.7425 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.6245 | 2.0 | 1000 | 0.6182 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.7026 | 3.0 | 1500 | 0.5939 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.6624 | 4.0 | 2000 | 0.5739 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.6389 | 5.0 | 2500 | 0.5673 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.6249 | 6.0 | 3000 | 0.5672 | 0.0 | 0.0 | 0.0 | 0.0 |
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.35.2
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- - Pytorch 2.1.0+cu118
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  - Datasets 2.15.0
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  - Tokenizers 0.15.0
 
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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-dataset4
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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: 0.5227
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+ - Accuracy: 0.212
 
 
 
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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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+ | 6.2329 | 1.0 | 250 | 1.3076 | 0.006 |
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+ | 1.6853 | 2.0 | 500 | 0.8967 | 0.09 |
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+ | 1.123 | 3.0 | 750 | 0.7346 | 0.132 |
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+ | 0.907 | 4.0 | 1000 | 0.6587 | 0.162 |
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+ | 0.7875 | 5.0 | 1250 | 0.6083 | 0.17 |
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+ | 0.7135 | 6.0 | 1500 | 0.5807 | 0.188 |
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+ | 0.675 | 7.0 | 1750 | 0.5566 | 0.196 |
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+ | 0.6403 | 8.0 | 2000 | 0.5427 | 0.206 |
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+ | 0.6229 | 9.0 | 2250 | 0.5354 | 0.208 |
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+ | 0.6046 | 10.0 | 2500 | 0.5329 | 0.212 |
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+ | 0.5974 | 11.0 | 2750 | 0.5237 | 0.212 |
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+ | 0.5875 | 12.0 | 3000 | 0.5227 | 0.212 |
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  ### Framework versions
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  - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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  - Datasets 2.15.0
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  - Tokenizers 0.15.0