---
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: 2.1310
- Exact Match: 0.4978
- F1: 0.6128

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-----------:|:------:|
| 0.7262        | 1.0   | 3182  | 1.2386          | 0.4634      | 0.5997 |
| 0.5564        | 2.0   | 6364  | 1.3796          | 0.4868      | 0.6083 |
| 0.4338        | 3.0   | 9546  | 1.5470          | 0.4864      | 0.6109 |
| 0.3148        | 4.0   | 12728 | 1.8582          | 0.5041      | 0.6141 |
| 0.2554        | 5.0   | 15910 | 2.1310          | 0.4978      | 0.6128 |


### Framework versions

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