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---
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
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