metadata

license: apache-2.0
base_model: om-ashish-soni/pos-morph-analysis-eng
tags:
  - generated_from_trainer
datasets:
  - universal_dependencies
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: pos-morph-analysis-eng
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: universal_dependencies
          type: universal_dependencies
          config: en_lines
          split: validation
          args: en_lines
        metrics:
          - name: Precision
            type: precision
            value: 0.9547287488574655
          - name: Recall
            type: recall
            value: 0.9594229522368706
          - name: F1
            type: f1
            value: 0.957070094591317
          - name: Accuracy
            type: accuracy
            value: 0.9573510302580286

pos-morph-analysis-eng

This model is a fine-tuned version of om-ashish-soni/pos-morph-analysis-eng on the universal_dependencies dataset. It achieves the following results on the evaluation set:

Loss: 0.2354
Precision: 0.9547
Recall: 0.9594
F1: 0.9571
Accuracy: 0.9574

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: 4
total_train_batch_size: 32
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	1.0	99	0.2425	0.9476	0.9523	0.9499	0.9505
No log	1.99	198	0.2253	0.9504	0.9553	0.9528	0.9540
No log	2.99	297	0.2273	0.9511	0.9565	0.9538	0.9548
No log	4.0	397	0.2348	0.9512	0.9559	0.9536	0.9541
No log	5.0	496	0.2294	0.9539	0.9586	0.9562	0.9574
0.0728	5.99	595	0.2319	0.9547	0.9594	0.9570	0.9574
0.0728	6.99	694	0.2405	0.9540	0.9585	0.9562	0.9566
0.0728	7.98	792	0.2354	0.9547	0.9594	0.9571	0.9574

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3