---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-NON-KD-SCR-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-SCR-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: 5.7960
- Accuracy: 0.3448
- F1: 0.3121

## 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  | 1.1461          | 0.3593   | 0.3245 |
| No log        | 3.45  | 200  | 1.9614          | 0.3611   | 0.3512 |
| No log        | 5.17  | 300  | 2.6180          | 0.3492   | 0.3157 |
| No log        | 6.9   | 400  | 3.1787          | 0.3673   | 0.3633 |
| 0.4792        | 8.62  | 500  | 3.7077          | 0.3527   | 0.3312 |
| 0.4792        | 10.34 | 600  | 4.5969          | 0.3549   | 0.3296 |
| 0.4792        | 12.07 | 700  | 4.8433          | 0.3483   | 0.3159 |
| 0.4792        | 13.79 | 800  | 5.1229          | 0.3602   | 0.3462 |
| 0.4792        | 15.52 | 900  | 5.3356          | 0.3554   | 0.3354 |
| 0.0195        | 17.24 | 1000 | 5.5333          | 0.3567   | 0.3421 |
| 0.0195        | 18.97 | 1100 | 5.4819          | 0.3660   | 0.3534 |
| 0.0195        | 20.69 | 1200 | 5.6908          | 0.3607   | 0.3366 |
| 0.0195        | 22.41 | 1300 | 5.7411          | 0.3483   | 0.3192 |
| 0.0195        | 24.14 | 1400 | 5.7830          | 0.3501   | 0.3217 |
| 0.0081        | 25.86 | 1500 | 5.8334          | 0.3457   | 0.3113 |
| 0.0081        | 27.59 | 1600 | 5.7030          | 0.3532   | 0.3299 |
| 0.0081        | 29.31 | 1700 | 5.7960          | 0.3448   | 0.3121 |


### Framework versions

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