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DaJulster
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Mental_health_response

Text2Text Generation
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t5
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text-generation-inference
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End of training

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  1. README.md +11 -8
  2. model.safetensors +1 -1
  3. runs/Mar31_05-13-08_a5b5045d4ed5/events.out.tfevents.1711861989.a5b5045d4ed5.35.1 +2 -2
README.md CHANGED
@@ -17,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.6565
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- - Rouge1: 0.0957
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- - Rouge2: 0.0189
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- - Rougel: 0.0745
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- - Rougelsum: 0.0745
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  - Gen Len: 19.0
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  ## Model description
@@ -47,15 +47,18 @@ 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: 2
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  - mixed_precision_training: Native AMP
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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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- | 3.4822 | 1.0 | 658 | 2.9374 | 0.0738 | 0.0103 | 0.0627 | 0.0627 | 19.0 |
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- | 2.8397 | 2.0 | 1316 | 2.6565 | 0.0957 | 0.0189 | 0.0745 | 0.0745 | 19.0 |
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.1482
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+ - Rouge1: 0.1071
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+ - Rouge2: 0.0265
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+ - Rougel: 0.0821
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+ - Rougelsum: 0.0823
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  - Gen Len: 19.0
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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: 5
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  - mixed_precision_training: Native AMP
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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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+ | 2.3526 | 1.0 | 658 | 2.7749 | 0.089 | 0.0141 | 0.0707 | 0.0707 | 19.0 |
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+ | 2.0919 | 2.0 | 1316 | 2.5361 | 0.1003 | 0.0202 | 0.0777 | 0.0778 | 19.0 |
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+ | 2.1006 | 3.0 | 1974 | 2.3129 | 0.1084 | 0.0209 | 0.0807 | 0.0808 | 19.0 |
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+ | 1.3701 | 4.0 | 2632 | 2.2004 | 0.1025 | 0.0213 | 0.0779 | 0.078 | 19.0 |
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+ | 1.0634 | 5.0 | 3290 | 2.1482 | 0.1071 | 0.0265 | 0.0821 | 0.0823 | 19.0 |
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  ### Framework versions
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