---
base_model: gechim/metadata-cls-no-gov-8k-v3
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhobertLexicalMeta-v2
  results: []
---

<!-- 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. -->

# PhobertLexicalMeta-v2

This model is a fine-tuned version of [gechim/metadata-cls-no-gov-8k-v3](https://huggingface.co/gechim/metadata-cls-no-gov-8k-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3926
- Accuracy: 0.9062
- F1: 0.8781

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.8772 | 100  | 0.2699          | 0.9080   | 0.8801 |
| 0.1564        | 1.7544 | 200  | 0.2984          | 0.9011   | 0.8723 |
| 0.073         | 2.6316 | 300  | 0.3218          | 0.8987   | 0.8705 |
| 0.0502        | 3.5088 | 400  | 0.3472          | 0.8927   | 0.8641 |
| 0.0326        | 4.3860 | 500  | 0.3627          | 0.8941   | 0.8635 |
| 0.0285        | 5.2632 | 600  | 0.3752          | 0.8964   | 0.8685 |
| 0.0179        | 6.1404 | 700  | 0.3666          | 0.9025   | 0.8734 |
| 0.0156        | 7.0175 | 800  | 0.3759          | 0.9043   | 0.8748 |
| 0.0156        | 7.8947 | 900  | 0.3830          | 0.9080   | 0.8788 |
| 0.011         | 8.7719 | 1000 | 0.3917          | 0.9039   | 0.8746 |
| 0.0092        | 9.6491 | 1100 | 0.3926          | 0.9062   | 0.8781 |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1