---
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-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: 5.0909
- Accuracy: 0.3682
- F1: 0.3646

## 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        | 1.7241  | 100  | 1.1864          | 0.3651   | 0.3644 |
| No log        | 3.4483  | 200  | 2.2167          | 0.3580   | 0.3355 |
| No log        | 5.1724  | 300  | 2.7873          | 0.3673   | 0.3618 |
| No log        | 6.8966  | 400  | 3.5495          | 0.3739   | 0.3714 |
| 0.4197        | 8.6207  | 500  | 4.2289          | 0.3770   | 0.3708 |
| 0.4197        | 10.3448 | 600  | 4.6578          | 0.3638   | 0.3605 |
| 0.4197        | 12.0690 | 700  | 4.5844          | 0.3690   | 0.3671 |
| 0.4197        | 13.7931 | 800  | 4.8103          | 0.3616   | 0.3462 |
| 0.4197        | 15.5172 | 900  | 4.8621          | 0.3616   | 0.3545 |
| 0.017         | 17.2414 | 1000 | 4.9407          | 0.3708   | 0.3657 |
| 0.017         | 18.9655 | 1100 | 5.0334          | 0.3699   | 0.3696 |
| 0.017         | 20.6897 | 1200 | 4.9701          | 0.3686   | 0.3676 |
| 0.017         | 22.4138 | 1300 | 4.9793          | 0.3686   | 0.3654 |
| 0.017         | 24.1379 | 1400 | 5.0299          | 0.3668   | 0.3600 |
| 0.0076        | 25.8621 | 1500 | 5.1558          | 0.3616   | 0.3544 |
| 0.0076        | 27.5862 | 1600 | 5.0915          | 0.3668   | 0.3622 |
| 0.0076        | 29.3103 | 1700 | 5.0909          | 0.3682   | 0.3646 |


### Framework versions

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