---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-finetuned-squad
  results: []
---

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# distilbert-base-uncased-finetuned-squad

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2104

## Model description

Most base model weights were frozen leaving only to finetune the last layer (qa outputs) and 3 last layers of the encoder.

## Training and evaluation data

Achieved EM: 73.519394512772, F1: 82.71779517079237

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.3937        | 1.0   | 5533  | 1.2915          |
| 1.1522        | 2.0   | 11066 | 1.2227          |
| 1.0055        | 3.0   | 16599 | 1.2104          |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3