---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: temp_assamese
  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. -->

# temp_assamese

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8132
- Accuracy: 0.8287

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.4466        | 0.0931 | 5000  | 1.5004          | 0.7075   |
| 1.4994        | 0.1862 | 10000 | 1.2256          | 0.7532   |
| 1.2888        | 0.2793 | 15000 | 1.0994          | 0.7766   |
| 1.1746        | 0.3723 | 20000 | 1.0090          | 0.7915   |
| 1.0994        | 0.4654 | 25000 | 0.9514          | 0.8021   |
| 1.0379        | 0.5585 | 30000 | 0.9029          | 0.8115   |
| 0.9956        | 0.6516 | 35000 | 0.8695          | 0.8174   |
| 0.9647        | 0.7447 | 40000 | 0.8462          | 0.8216   |
| 0.9351        | 0.8378 | 45000 | 0.8274          | 0.8258   |
| 0.9194        | 0.9309 | 50000 | 0.8120          | 0.8286   |


### Framework versions

- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1