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FLANT5_base

Text2Text Generation
Transformers
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Safetensors
t5
Generated from Trainer
text-generation-inference
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End of training

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  1. README.md +11 -10
  2. logs/events.out.tfevents.1728108858.0310f89d347d.2982.0 +2 -2
README.md CHANGED
@@ -19,12 +19,12 @@ 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: 0.1032
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- - Bleu Score: 24.5858
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- - Precision: 5.6153
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- - Recall: 5.6153
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- - Gen Len: 18.81
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- - Err: 5.6153
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  ## Model description
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@@ -49,15 +49,16 @@ The following hyperparameters were used during training:
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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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall | Gen Len | Err |
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  |:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:------:|:-------:|:------:|
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- | 0.2198 | 1.0 | 838 | 0.1347 | 23.608 | 4.779 | 4.779 | 18.7897 | 4.779 |
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- | 0.1309 | 2.0 | 1676 | 0.1099 | 24.3086 | 5.3763 | 5.3763 | 18.8088 | 5.3763 |
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- | 0.1079 | 3.0 | 2514 | 0.1032 | 24.5858 | 5.6153 | 5.6153 | 18.81 | 5.6153 |
 
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  ### Framework versions
 
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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: 0.0941
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+ - Bleu Score: 24.8094
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+ - Precision: 6.0932
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+ - Recall: 6.0932
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+ - Gen Len: 18.8172
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+ - Err: 6.0932
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  ## Model description
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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: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall | Gen Len | Err |
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  |:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:------:|:-------:|:------:|
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+ | 0.2195 | 1.0 | 838 | 0.1354 | 23.689 | 5.0179 | 5.0179 | 18.7945 | 5.0179 |
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+ | 0.1289 | 2.0 | 1676 | 0.1085 | 24.4546 | 5.7348 | 5.7348 | 18.8053 | 5.7348 |
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+ | 0.104 | 3.0 | 2514 | 0.0969 | 24.8285 | 6.0932 | 6.0932 | 18.8112 | 6.0932 |
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+ | 0.0906 | 4.0 | 3352 | 0.0941 | 24.8094 | 6.0932 | 6.0932 | 18.8172 | 6.0932 |
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  ### Framework versions
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