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

README.md

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+---
+license: apache-2.0
+base_model: om-ashish-soni/pos-ner-tagging-v3
+tags:
+- generated_from_trainer
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: pos-ner-tagging-v4
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      config: conll2003
+      split: validation
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9242642437694764
+    - name: Recall
+      type: recall
+      value: 0.9264290339671514
+    - name: F1
+      type: f1
+      value: 0.9244306954134476
+    - name: Accuracy
+      type: accuracy
+      value: 0.9264290339671514
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# pos-ner-tagging-v4
+
+This model is a fine-tuned version of [om-ashish-soni/pos-ner-tagging-v3](https://huggingface.co/om-ashish-soni/pos-ner-tagging-v3) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6642
+- Precision: 0.9243
+- Recall: 0.9264
+- F1: 0.9244
+- Accuracy: 0.9264
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.98  | 54   | 0.6425          | 0.9254    | 0.9272 | 0.9250 | 0.9272   |
+| No log        | 1.99  | 109  | 0.6624          | 0.9239    | 0.9261 | 0.9240 | 0.9261   |
+| No log        | 2.99  | 164  | 0.6593          | 0.9245    | 0.9267 | 0.9245 | 0.9267   |
+| No log        | 3.99  | 219  | 0.6608          | 0.9251    | 0.9270 | 0.9250 | 0.9270   |
+| No log        | 4.99  | 274  | 0.6698          | 0.9246    | 0.9269 | 0.9245 | 0.9269   |
+| No log        | 6.0   | 329  | 0.6648          | 0.9246    | 0.9264 | 0.9244 | 0.9264   |
+| No log        | 7.0   | 384  | 0.6651          | 0.9244    | 0.9266 | 0.9245 | 0.9266   |
+| No log        | 7.87  | 432  | 0.6642          | 0.9243    | 0.9264 | 0.9244 | 0.9264   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3