---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: MRC_ER_mdeberta-v3-base_syl_DSC
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# MRC_ER_mdeberta-v3-base_syl_DSC

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: 1.9616
- Exact Match: 0.4925
- F1: 0.5963

## 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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Exact Match | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:-----------:|:------:|
| 0.7001        | 1.0   | 3097  | 1.2355          | 0.4420      | 0.5752 |
| 0.5383        | 2.0   | 6194  | 1.4327          | 0.4784      | 0.5984 |
| 0.4088        | 3.0   | 9291  | 1.6247          | 0.4762      | 0.5947 |
| 0.282         | 4.0   | 12388 | 1.6999          | 0.4895      | 0.5986 |
| 0.2361        | 5.0   | 15485 | 1.9616          | 0.4925      | 0.5963 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1