---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-NON-KD-PR-COPY-CDF-EN-D2_data-en-cardiff_eng_only44
  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. -->

# scenario-NON-KD-PR-COPY-CDF-EN-D2_data-en-cardiff_eng_only44

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3429
- Accuracy: 0.4330
- F1: 0.4179

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 44
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.72  | 100  | 1.1160          | 0.4074   | 0.3433 |
| No log        | 3.45  | 200  | 1.2658          | 0.4149   | 0.3707 |
| No log        | 5.17  | 300  | 1.7230          | 0.4599   | 0.4582 |
| No log        | 6.9   | 400  | 1.7742          | 0.4383   | 0.4266 |
| 0.6464        | 8.62  | 500  | 2.4181          | 0.4334   | 0.4215 |
| 0.6464        | 10.34 | 600  | 2.9688          | 0.4444   | 0.4397 |
| 0.6464        | 12.07 | 700  | 3.2008          | 0.4374   | 0.4342 |
| 0.6464        | 13.79 | 800  | 4.2300          | 0.4233   | 0.4012 |
| 0.6464        | 15.52 | 900  | 4.2439          | 0.4414   | 0.4382 |
| 0.0996        | 17.24 | 1000 | 4.6596          | 0.4506   | 0.4385 |
| 0.0996        | 18.97 | 1100 | 4.7742          | 0.4343   | 0.4252 |
| 0.0996        | 20.69 | 1200 | 4.9060          | 0.4440   | 0.4336 |
| 0.0996        | 22.41 | 1300 | 5.0117          | 0.4365   | 0.4288 |
| 0.0996        | 24.14 | 1400 | 5.0594          | 0.4444   | 0.4348 |
| 0.0222        | 25.86 | 1500 | 5.1602          | 0.4440   | 0.4351 |
| 0.0222        | 27.59 | 1600 | 5.2402          | 0.4405   | 0.4325 |
| 0.0222        | 29.31 | 1700 | 5.3429          | 0.4330   | 0.4179 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3