---
base_model: microsoft/mdeberta-v3-base
library_name: transformers
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: scenario-NON-KD-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_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-CL-D2_data-cl-cardiff_cl_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: 6.2603
- Accuracy: 0.3657
- F1: 0.3633

## 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        | 1.0870  | 250  | 1.3365          | 0.3519   | 0.3479 |
| 0.9017        | 2.1739  | 500  | 1.9777          | 0.3565   | 0.3508 |
| 0.9017        | 3.2609  | 750  | 2.9438          | 0.3542   | 0.3298 |
| 0.3023        | 4.3478  | 1000 | 3.1702          | 0.3611   | 0.3489 |
| 0.3023        | 5.4348  | 1250 | 3.4689          | 0.3534   | 0.3522 |
| 0.1011        | 6.5217  | 1500 | 4.0537          | 0.3627   | 0.3608 |
| 0.1011        | 7.6087  | 1750 | 4.5352          | 0.3573   | 0.3504 |
| 0.0549        | 8.6957  | 2000 | 4.5030          | 0.3495   | 0.3449 |
| 0.0549        | 9.7826  | 2250 | 4.6084          | 0.3519   | 0.3479 |
| 0.0339        | 10.8696 | 2500 | 4.7223          | 0.3565   | 0.3505 |
| 0.0339        | 11.9565 | 2750 | 4.9936          | 0.3565   | 0.3518 |
| 0.0232        | 13.0435 | 3000 | 4.5828          | 0.3449   | 0.3352 |
| 0.0232        | 14.1304 | 3250 | 5.0265          | 0.3565   | 0.3543 |
| 0.0224        | 15.2174 | 3500 | 5.2273          | 0.3627   | 0.3580 |
| 0.0224        | 16.3043 | 3750 | 5.2708          | 0.3611   | 0.3516 |
| 0.0156        | 17.3913 | 4000 | 5.6845          | 0.3511   | 0.3469 |
| 0.0156        | 18.4783 | 4250 | 5.5643          | 0.3603   | 0.3537 |
| 0.0081        | 19.5652 | 4500 | 5.9288          | 0.3519   | 0.3372 |
| 0.0081        | 20.6522 | 4750 | 5.9406          | 0.3611   | 0.3564 |
| 0.0034        | 21.7391 | 5000 | 5.9909          | 0.3534   | 0.3519 |
| 0.0034        | 22.8261 | 5250 | 6.1283          | 0.3611   | 0.3562 |
| 0.0017        | 23.9130 | 5500 | 6.1721          | 0.3688   | 0.3668 |
| 0.0017        | 25.0    | 5750 | 6.2167          | 0.3596   | 0.3581 |
| 0.0019        | 26.0870 | 6000 | 6.2126          | 0.3627   | 0.3596 |
| 0.0019        | 27.1739 | 6250 | 6.2446          | 0.3634   | 0.3616 |
| 0.0014        | 28.2609 | 6500 | 6.2484          | 0.3650   | 0.3624 |
| 0.0014        | 29.3478 | 6750 | 6.2603          | 0.3657   | 0.3633 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1