---
license: apache-2.0
base_model: distilbert-base-uncased-distilled-squad
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: gmra_model_distilbert-base-uncased-distilled-squad_17082023T150913
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gmra_model_distilbert-base-uncased-distilled-squad_17082023T150913

This model is a fine-tuned version of [distilbert-base-uncased-distilled-squad](https://huggingface.co/distilbert-base-uncased-distilled-squad) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6179
- Accuracy: 0.2575
- F1: 0.0683

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 142  | 1.6182          | 0.2575   | 0.0683 |
| No log        | 2.0   | 284  | 1.6184          | 0.2575   | 0.0683 |
| No log        | 2.99  | 426  | 1.6182          | 0.2575   | 0.0683 |
| 1.6013        | 4.0   | 569  | 1.6181          | 0.2575   | 0.0683 |
| 1.6013        | 5.0   | 711  | 1.6182          | 0.2575   | 0.0683 |
| 1.6013        | 6.0   | 853  | 1.6179          | 0.2575   | 0.0683 |
| 1.6013        | 6.99  | 995  | 1.6180          | 0.2575   | 0.0683 |
| 1.6032        | 8.0   | 1138 | 1.6179          | 0.2575   | 0.0683 |
| 1.6032        | 9.0   | 1280 | 1.6177          | 0.2575   | 0.0683 |
| 1.6032        | 9.98  | 1420 | 1.6179          | 0.2575   | 0.0683 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3