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RafaelMayer
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copec-whatsapp-13-roberta

Text Classification
Transformers
TensorFlow
roberta
generated_from_keras_callback
Inference Endpoints
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RafaelMayer commited on
Commit
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1 Parent(s): 8a929e9

Training in progress epoch 9

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Files changed (2) hide show
  1. README.md +9 -3
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -15,8 +15,8 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.6808
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- - Validation Loss: 0.6818
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  - Train Accuracy: 0.7647
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  - Train Precision: [0. 0.76470588]
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  - Train Precision W: 0.5848
@@ -24,7 +24,7 @@ It achieves the following results on the evaluation set:
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  - Train Recall W: 0.7647
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  - Train F1: [0. 0.86666667]
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  - Train F1 W: 0.6627
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- - Epoch: 3
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  ## Model description
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@@ -53,6 +53,12 @@ The following hyperparameters were used during training:
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  | 0.6829 | 0.6850 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 1 |
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  | 0.6834 | 0.6838 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 2 |
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  | 0.6808 | 0.6818 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 3 |
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.6498
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+ - Validation Loss: 0.6487
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  - Train Accuracy: 0.7647
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  - Train Precision: [0. 0.76470588]
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  - Train Precision W: 0.5848
 
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  - Train Recall W: 0.7647
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  - Train F1: [0. 0.86666667]
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  - Train F1 W: 0.6627
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+ - Epoch: 9
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  ## Model description
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  | 0.6829 | 0.6850 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 1 |
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  | 0.6834 | 0.6838 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 2 |
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  | 0.6808 | 0.6818 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 3 |
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+ | 0.6787 | 0.6790 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 4 |
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+ | 0.6743 | 0.6753 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 5 |
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+ | 0.6684 | 0.6706 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 6 |
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+ | 0.6643 | 0.6647 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 7 |
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+ | 0.6522 | 0.6576 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 8 |
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+ | 0.6498 | 0.6487 | 0.7647 | [0. 0.76470588] | 0.5848 | [0. 1.] | 0.7647 | [0. 0.86666667] | 0.6627 | 9 |
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  ### Framework versions
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