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alibidaran
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t5-small-medical_transcription

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Transformers
PyTorch
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t5
text2text-generation
Generated from Trainer
text-generation-inference
Inference Endpoints
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update model card README.md

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@@ -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 [t5-small](https://huggingface.co/t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.7744
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- - Rouge1: 0.3722
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- - Rouge2: 0.2709
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- - Rougel: 0.3628
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- - Rougelsum: 0.3619
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- - Gen Len: 17.0877
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  ## Model description
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@@ -47,20 +47,22 @@ 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: 8
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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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- | 2.4475 | 1.0 | 27 | 2.0647 | 0.3288 | 0.2503 | 0.3252 | 0.3212 | 17.2281 |
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- | 2.0319 | 2.0 | 54 | 1.9089 | 0.3456 | 0.2527 | 0.3407 | 0.3377 | 16.3684 |
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- | 1.8772 | 3.0 | 81 | 1.8572 | 0.3528 | 0.2615 | 0.3478 | 0.3457 | 16.1579 |
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- | 1.796 | 4.0 | 108 | 1.8211 | 0.3274 | 0.2479 | 0.324 | 0.3216 | 15.7719 |
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- | 1.7107 | 5.0 | 135 | 1.7972 | 0.3689 | 0.277 | 0.3614 | 0.3586 | 16.3509 |
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- | 1.711 | 6.0 | 162 | 1.7852 | 0.359 | 0.2599 | 0.3505 | 0.348 | 16.2105 |
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- | 1.7581 | 7.0 | 189 | 1.7773 | 0.3659 | 0.2646 | 0.3566 | 0.3559 | 16.9298 |
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- | 1.704 | 8.0 | 216 | 1.7744 | 0.3722 | 0.2709 | 0.3628 | 0.3619 | 17.0877 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2564
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+ - Rouge1: 0.4958
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+ - Rouge2: 0.419
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+ - Rougel: 0.4803
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+ - Rougelsum: 0.481
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+ - Gen Len: 18.1147
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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: 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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+ | 0.8608 | 1.0 | 559 | 0.3784 | 0.4243 | 0.3455 | 0.4076 | 0.4084 | 17.7384 |
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+ | 0.4157 | 2.0 | 1118 | 0.3419 | 0.4245 | 0.3503 | 0.4092 | 0.4101 | 17.8612 |
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+ | 0.3736 | 3.0 | 1677 | 0.3110 | 0.4436 | 0.3699 | 0.4274 | 0.4282 | 18.1187 |
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+ | 0.3491 | 4.0 | 2236 | 0.3016 | 0.4613 | 0.3882 | 0.4452 | 0.4465 | 18.163 |
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+ | 0.3253 | 5.0 | 2795 | 0.2844 | 0.4702 | 0.3962 | 0.4542 | 0.4545 | 18.1187 |
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+ | 0.3094 | 6.0 | 3354 | 0.2735 | 0.4767 | 0.403 | 0.4607 | 0.4612 | 18.1308 |
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+ | 0.2983 | 7.0 | 3913 | 0.2652 | 0.4853 | 0.4099 | 0.4692 | 0.4699 | 18.0201 |
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+ | 0.2908 | 8.0 | 4472 | 0.2601 | 0.494 | 0.4175 | 0.4775 | 0.4783 | 18.1247 |
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+ | 0.2808 | 9.0 | 5031 | 0.2571 | 0.4954 | 0.4169 | 0.4799 | 0.4811 | 18.0926 |
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+ | 0.2803 | 10.0 | 5590 | 0.2564 | 0.4958 | 0.419 | 0.4803 | 0.481 | 18.1147 |
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  ### Framework versions