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---
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
---
<!-- 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-morph-analysis-eng
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.
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
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