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FLANT5_base

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

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  2. logs/events.out.tfevents.1727588001.e82bdb3be7ef.1920.0 +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: 0.1150
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- - Bleu Score: 24.3919
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- - Precision: 5.3763
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- - Recall: 5.3763
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- - Gen Len: 18.8088
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- - Err: 5.3763
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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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- | 0.2345 | 1.0 | 419 | 0.1435 | 23.524 | 3.9427 | 3.9427 | 18.8112 | 3.9427 |
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- | 0.1464 | 2.0 | 838 | 0.1197 | 24.2187 | 5.4958 | 5.4958 | 18.8053 | 5.4958 |
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- | 0.1238 | 3.0 | 1257 | 0.1150 | 24.3919 | 5.3763 | 5.3763 | 18.8088 | 5.3763 |
 
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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: 0.1042
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+ - Bleu Score: 24.572
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+ - Precision: 5.4958
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+ - Recall: 5.4958
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+ - Gen Len: 18.816
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+ - Err: 5.4958
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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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+ | 0.2337 | 1.0 | 419 | 0.1422 | 23.5468 | 4.0621 | 4.0621 | 18.8088 | 4.0621 |
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+ | 0.1441 | 2.0 | 838 | 0.1186 | 24.2904 | 5.4958 | 5.4958 | 18.8041 | 5.4958 |
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+ | 0.1185 | 3.0 | 1257 | 0.1077 | 24.4658 | 5.3763 | 5.3763 | 18.8124 | 5.3763 |
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+ | 0.1069 | 4.0 | 1676 | 0.1042 | 24.572 | 5.4958 | 5.4958 | 18.816 | 5.4958 |
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  ### Framework versions
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