---
library_name: transformers
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: mdeberta-domain_fold2
  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. -->

# mdeberta-domain_fold2

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: 0.3971
- Accuracy: 0.925
- Precision: 0.9478
- Recall: 0.6667
- F1: 0.6393

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 5    | 1.0148          | 0.525    | 0.8417    | 0.3333 | 0.2295 |
| 1.0205        | 2.0   | 10   | 0.9308          | 0.525    | 0.8417    | 0.3333 | 0.2295 |
| 1.0205        | 3.0   | 15   | 0.8402          | 0.525    | 0.8417    | 0.3333 | 0.2295 |
| 0.8453        | 4.0   | 20   | 0.7396          | 0.525    | 0.8417    | 0.3333 | 0.2295 |
| 0.8453        | 5.0   | 25   | 0.6271          | 0.825    | 0.8883    | 0.5833 | 0.5645 |
| 0.6618        | 6.0   | 30   | 0.5737          | 0.825    | 0.8883    | 0.5833 | 0.5645 |
| 0.6618        | 7.0   | 35   | 0.4670          | 0.9      | 0.9318    | 0.6458 | 0.6212 |
| 0.4922        | 8.0   | 40   | 0.4277          | 0.925    | 0.9478    | 0.6667 | 0.6393 |
| 0.4922        | 9.0   | 45   | 0.4040          | 0.925    | 0.9478    | 0.6667 | 0.6393 |
| 0.4176        | 10.0  | 50   | 0.3971          | 0.925    | 0.9478    | 0.6667 | 0.6393 |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.20.1