om-ashish-soni
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Shree Ganeshay Namah, POS-MORPH Training with seqeval metrics complete
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README.md
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metrics:
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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- name: F1
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type: f1
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value: 0.
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- name: Accuracy
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type: accuracy
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value: 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 [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.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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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:
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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.
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| No log | 1.99 | 198 | 0.
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| No log | 2.99 | 297 | 0.
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| No log |
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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
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