---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
- precision
model-index:
- name: mdeberta-v3-base-fine-tuned-text-classificarion-ds-ss
  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-v3-base-fine-tuned-text-classificarion-ds-ss

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: 1.0388
- F1: 0.7346
- Recall: 0.7570
- Accuracy: 0.7570
- Precision: 0.7456

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Recall | Accuracy | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:---------:|
| 3.3067        | 1.0   | 883  | 1.8916          | 0.4861 | 0.5479 | 0.5479   | 0.4605    |
| 1.5839        | 2.0   | 1766 | 1.2443          | 0.6494 | 0.6955 | 0.6955   | 0.6456    |
| 1.1286        | 3.0   | 2649 | 1.0806          | 0.7047 | 0.7283 | 0.7283   | 0.7074    |
| 0.892         | 4.0   | 3532 | 1.0966          | 0.7087 | 0.7393 | 0.7393   | 0.7165    |
| 0.7316        | 5.0   | 4415 | 1.0388          | 0.7346 | 0.7570 | 0.7570   | 0.7456    |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3