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Shree Ganeshay Namah, POS-MORPH Training with seqeval metrics complete

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  1. README.md +18 -14
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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: 0.9470202237521514
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  - name: Recall
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  type: recall
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- value: 0.951318348822131
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  - name: F1
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  type: f1
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- value: 0.9491644204851751
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  - name: Accuracy
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  type: accuracy
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- value: 0.9499257471691108
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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 [om-ashish-soni/pos-morph-analysis-eng](https://huggingface.co/om-ashish-soni/pos-morph-analysis-eng) on the universal_dependencies dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2405
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- - Precision: 0.9470
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- - Recall: 0.9513
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- - F1: 0.9492
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- - Accuracy: 0.9499
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  ## Model description
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@@ -75,16 +75,20 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 32
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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: 4
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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 | 99 | 0.3058 | 0.9324 | 0.9376 | 0.9350 | 0.9369 |
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- | No log | 1.99 | 198 | 0.2559 | 0.9423 | 0.9461 | 0.9442 | 0.9456 |
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- | No log | 2.99 | 297 | 0.2424 | 0.9449 | 0.9497 | 0.9473 | 0.9488 |
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- | No log | 3.99 | 396 | 0.2405 | 0.9470 | 0.9513 | 0.9492 | 0.9499 |
 
 
 
 
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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: 0.9547287488574655
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  - name: Recall
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  type: recall
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+ value: 0.9594229522368706
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  - name: F1
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  type: f1
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+ value: 0.957070094591317
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9573510302580286
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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 [om-ashish-soni/pos-morph-analysis-eng](https://huggingface.co/om-ashish-soni/pos-morph-analysis-eng) on the universal_dependencies dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2354
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+ - Precision: 0.9547
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+ - Recall: 0.9594
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+ - F1: 0.9571
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+ - Accuracy: 0.9574
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  ## Model description
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  - total_train_batch_size: 32
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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: 8
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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 | 99 | 0.2425 | 0.9476 | 0.9523 | 0.9499 | 0.9505 |
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+ | No log | 1.99 | 198 | 0.2253 | 0.9504 | 0.9553 | 0.9528 | 0.9540 |
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+ | No log | 2.99 | 297 | 0.2273 | 0.9511 | 0.9565 | 0.9538 | 0.9548 |
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+ | No log | 4.0 | 397 | 0.2348 | 0.9512 | 0.9559 | 0.9536 | 0.9541 |
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+ | No log | 5.0 | 496 | 0.2294 | 0.9539 | 0.9586 | 0.9562 | 0.9574 |
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+ | 0.0728 | 5.99 | 595 | 0.2319 | 0.9547 | 0.9594 | 0.9570 | 0.9574 |
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+ | 0.0728 | 6.99 | 694 | 0.2405 | 0.9540 | 0.9585 | 0.9562 | 0.9566 |
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+ | 0.0728 | 7.98 | 792 | 0.2354 | 0.9547 | 0.9594 | 0.9571 | 0.9574 |
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  ### Framework versions