---
library_name: transformers
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_07112024T110436
  results: []
---

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# gmra_model_distilbert-base-uncased-distilled-squad_07112024T110436

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: 0.3023
- Accuracy: 94.1125
- F1: 0.9587

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.9982 | 142  | 0.3683          | 88.0492  | 0.7519 |
| No log        | 1.9965 | 284  | 0.2634          | 91.5641  | 0.9238 |
| No log        | 2.9947 | 426  | 0.2386          | 92.8822  | 0.9432 |
| 0.3507        | 4.0    | 569  | 0.2321          | 93.9367  | 0.9579 |
| 0.3507        | 4.9982 | 711  | 0.2897          | 93.4095  | 0.9536 |
| 0.3507        | 5.9965 | 853  | 0.2745          | 94.2882  | 0.9606 |
| 0.3507        | 6.9947 | 995  | 0.2892          | 94.3761  | 0.9616 |
| 0.0379        | 8.0    | 1138 | 0.3055          | 94.0246  | 0.9579 |
| 0.0379        | 8.9982 | 1280 | 0.3144          | 93.7610  | 0.9562 |
| 0.0379        | 9.9824 | 1420 | 0.3023          | 94.1125  | 0.9587 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1