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Venkatesh4342
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deberta-v3-base-Whatsapp-ner

Token Classification
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deberta-v2
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End of training

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  1. README.md +11 -11
  2. runs/Mar31_13-58-49_fa34a42b14f0/events.out.tfevents.1711893537.fa34a42b14f0.186.0 +2 -2
  3. runs/Mar31_13-58-49_fa34a42b14f0/events.out.tfevents.1711893742.fa34a42b14f0.186.1 +3 -0
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0281
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- - Precision: 0.9483
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  - Recall: 0.9649
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- - F1: 0.9565
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- - Accuracy: 0.9881
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  ## Model description
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@@ -43,7 +43,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 42
@@ -55,12 +55,12 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 58 | 0.1096 | 0.8852 | 0.9474 | 0.9153 | 0.9711 |
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- | No log | 2.0 | 116 | 0.0573 | 0.9569 | 0.9737 | 0.9652 | 0.9830 |
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- | No log | 3.0 | 174 | 0.0444 | 0.9402 | 0.9649 | 0.9524 | 0.9830 |
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- | No log | 4.0 | 232 | 0.0272 | 0.9402 | 0.9649 | 0.9524 | 0.9864 |
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- | No log | 5.0 | 290 | 0.0322 | 0.9402 | 0.9649 | 0.9524 | 0.9864 |
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- | No log | 6.0 | 348 | 0.0281 | 0.9483 | 0.9649 | 0.9565 | 0.9881 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0904
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+ - Precision: 0.9322
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  - Recall: 0.9649
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+ - F1: 0.9483
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+ - Accuracy: 0.9813
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 58 | 0.1103 | 0.9316 | 0.9561 | 0.9437 | 0.9762 |
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+ | No log | 2.0 | 116 | 0.1157 | 0.9474 | 0.9474 | 0.9474 | 0.9796 |
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+ | No log | 3.0 | 174 | 0.1069 | 0.9153 | 0.9474 | 0.9310 | 0.9779 |
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+ | No log | 4.0 | 232 | 0.0904 | 0.9322 | 0.9649 | 0.9483 | 0.9813 |
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+ | No log | 5.0 | 290 | 0.0990 | 0.9322 | 0.9649 | 0.9483 | 0.9796 |
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+ | No log | 6.0 | 348 | 0.0964 | 0.9244 | 0.9649 | 0.9442 | 0.9813 |
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  ### Framework versions
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