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t5-base_cola_dense_epochs-3

Text Classification
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
Model card Files Community
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End of training

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  1. README.md +19 -19
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8264621284755513
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the glue dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4436
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- - Accuracy: 0.8265
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  ## Model description
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@@ -65,22 +65,22 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.5779 | 0.19 | 50 | 0.5663 | 0.6913 |
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- | 0.4499 | 0.37 | 100 | 0.5698 | 0.7689 |
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- | 0.4599 | 0.56 | 150 | 0.4754 | 0.7996 |
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- | 0.3906 | 0.75 | 200 | 0.4966 | 0.8102 |
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- | 0.474 | 0.93 | 250 | 0.5193 | 0.8092 |
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- | 0.3694 | 1.12 | 300 | 0.4917 | 0.8245 |
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- | 0.3585 | 1.31 | 350 | 0.4704 | 0.8226 |
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- | 0.3412 | 1.49 | 400 | 0.4762 | 0.8207 |
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- | 0.429 | 1.68 | 450 | 0.4945 | 0.8245 |
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- | 0.3743 | 1.87 | 500 | 0.4436 | 0.8265 |
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- | 0.3028 | 2.05 | 550 | 0.5025 | 0.8265 |
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- | 0.3253 | 2.24 | 600 | 0.5310 | 0.8245 |
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- | 0.2961 | 2.43 | 650 | 0.4966 | 0.8303 |
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- | 0.2434 | 2.61 | 700 | 0.5028 | 0.8293 |
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- | 0.3262 | 2.8 | 750 | 0.5044 | 0.8284 |
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- | 0.2562 | 2.99 | 800 | 0.4945 | 0.8274 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8283796740172579
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the glue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5042
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+ - Accuracy: 0.8284
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5796 | 0.19 | 50 | 0.5780 | 0.6913 |
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+ | 0.4821 | 0.37 | 100 | 0.6683 | 0.7546 |
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+ | 0.4703 | 0.56 | 150 | 0.4976 | 0.8035 |
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+ | 0.4252 | 0.75 | 200 | 0.4958 | 0.8150 |
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+ | 0.4915 | 0.93 | 250 | 0.5360 | 0.8044 |
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+ | 0.3812 | 1.12 | 300 | 0.4645 | 0.8322 |
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+ | 0.3603 | 1.31 | 350 | 0.4788 | 0.8293 |
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+ | 0.3336 | 1.49 | 400 | 0.5135 | 0.8245 |
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+ | 0.4157 | 1.68 | 450 | 0.5311 | 0.8322 |
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+ | 0.4094 | 1.87 | 500 | 0.5042 | 0.8284 |
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+ | 0.2836 | 2.05 | 550 | 0.5277 | 0.8313 |
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+ | 0.2993 | 2.24 | 600 | 0.5515 | 0.8341 |
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+ | 0.2843 | 2.43 | 650 | 0.5195 | 0.8332 |
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+ | 0.2288 | 2.61 | 700 | 0.5129 | 0.8332 |
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+ | 0.3165 | 2.8 | 750 | 0.5126 | 0.8360 |
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+ | 0.2717 | 2.99 | 800 | 0.5083 | 0.8332 |
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  ### Framework versions