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End of training

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  1. README.md +16 -16
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@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.7241379310344828
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  - name: Recall
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  type: recall
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- value: 0.7170731707317073
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  - name: F1
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  type: f1
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- value: 0.7205882352941175
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  - name: Accuracy
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  type: accuracy
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- value: 0.9920721492851299
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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
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indian_names dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0278
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- - Precision: 0.7241
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- - Recall: 0.7171
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- - F1: 0.7206
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- - Accuracy: 0.9921
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  ## Model description
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@@ -77,13 +77,13 @@ The following hyperparameters were used during training:
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  ### Training results
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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 | 63 | 0.1197 | 0.0 | 0.0 | 0.0 | 0.9745 |
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- | No log | 2.0 | 126 | 0.0818 | 0.8438 | 0.0263 | 0.0511 | 0.9751 |
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- | No log | 3.0 | 189 | 0.0470 | 0.5270 | 0.4859 | 0.5056 | 0.9857 |
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- | No log | 4.0 | 252 | 0.0315 | 0.7042 | 0.6341 | 0.6674 | 0.9906 |
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- | No log | 5.0 | 315 | 0.0278 | 0.7241 | 0.7171 | 0.7206 | 0.9921 |
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 1.0
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  - name: Recall
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  type: recall
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+ value: 1.0
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  - name: F1
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  type: f1
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+ value: 1.0
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  - name: Accuracy
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  type: accuracy
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+ value: 1.0
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indian_names dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0
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+ - Precision: 1.0
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+ - Recall: 1.0
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+ - F1: 1.0
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+ - Accuracy: 1.0
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  ## Model description
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  ### Training results
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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 | 1 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 2.0 | 2 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 3.0 | 3 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 4.0 | 4 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 5.0 | 5 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions