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Floyd93
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FlanT5_Grammar_Correction

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text2text-generation
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  1. README.md +22 -13
  2. logs/events.out.tfevents.1703910796.ff7645398067.5934.0 +2 -2
  3. logs/events.out.tfevents.1703951093.ff7645398067.5934.1 +3 -0
  4. model.safetensors +1 -1
README.md CHANGED
@@ -17,12 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8955
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- - Rouge1: 16.29
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- - Rouge2: 13.1077
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- - Rougel: 16.322
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- - Rougelsum: 16.301
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- - Gen Len: 19.0
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  ## Model description
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@@ -42,23 +42,32 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 1
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- - eval_batch_size: 1
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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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  ### 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 | 70 | 0.8955 | 16.29 | 13.1077 | 16.322 | 16.301 | 19.0 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.36.2
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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
 
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  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5641
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+ - Rouge1: 25.8411
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+ - Rouge2: 21.9266
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+ - Rougel: 25.6021
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+ - Rougelsum: 25.8204
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+ - Gen Len: 18.66
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 10
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+ - eval_batch_size: 10
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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: 10
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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 | 70 | 0.6908 | 24.6523 | 20.2616 | 24.4437 | 24.5628 | 18.7067 |
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+ | No log | 2.0 | 140 | 0.6518 | 24.8929 | 20.7179 | 24.6941 | 24.82 | 18.6933 |
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+ | No log | 3.0 | 210 | 0.6094 | 25.3966 | 21.4469 | 25.1476 | 25.3394 | 18.66 |
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+ | No log | 4.0 | 280 | 0.6017 | 25.6059 | 21.6233 | 25.3733 | 25.602 | 18.65 |
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+ | No log | 5.0 | 350 | 0.5839 | 25.6422 | 21.6618 | 25.399 | 25.6115 | 18.6533 |
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+ | No log | 6.0 | 420 | 0.5743 | 25.6713 | 21.6384 | 25.4196 | 25.645 | 18.6533 |
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+ | No log | 7.0 | 490 | 0.5710 | 25.7888 | 21.8155 | 25.5426 | 25.7576 | 18.6667 |
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+ | 0.7559 | 8.0 | 560 | 0.5669 | 25.8358 | 21.8943 | 25.5741 | 25.8059 | 18.6667 |
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+ | 0.7559 | 9.0 | 630 | 0.5651 | 25.8471 | 21.9295 | 25.606 | 25.8206 | 18.66 |
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+ | 0.7559 | 10.0 | 700 | 0.5641 | 25.8411 | 21.9266 | 25.6021 | 25.8204 | 18.66 |
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  ### Framework versions
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  - Transformers 4.36.2
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.0
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  - Tokenizers 0.15.0
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