---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased-distilled-squad
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: b3e36b8ecaa0de9195fc36f8913303b8
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# b3e36b8ecaa0de9195fc36f8913303b8

This model is a fine-tuned version of [distilbert/distilbert-base-uncased-distilled-squad](https://huggingface.co/distilbert/distilbert-base-uncased-distilled-squad) on the contemmcm/trec dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2582
- Data Size: 1.0
- Epoch Runtime: 5.4157
- Accuracy: 0.9667
- F1 Macro: 0.9567

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
| No log        | 0     | 0    | 1.8271          | 0         | 0.7633        | 0.1021   | 0.0430   |
| No log        | 1     | 170  | 1.6646          | 0.0078    | 0.9938        | 0.3583   | 0.1980   |
| No log        | 2     | 340  | 1.5154          | 0.0156    | 1.0284        | 0.5333   | 0.4079   |
| No log        | 3     | 510  | 1.1134          | 0.0312    | 1.1448        | 0.9021   | 0.7548   |
| No log        | 4     | 680  | 0.5776          | 0.0625    | 1.2973        | 0.9104   | 0.7653   |
| 0.0547        | 5     | 850  | 0.2355          | 0.125     | 1.7117        | 0.9521   | 0.8007   |
| 0.0547        | 6     | 1020 | 0.2012          | 0.25      | 2.1348        | 0.9542   | 0.9309   |
| 0.2029        | 7     | 1190 | 0.2062          | 0.5       | 3.2885        | 0.9563   | 0.9313   |
| 0.141         | 8.0   | 1360 | 0.1672          | 1.0       | 5.5069        | 0.9625   | 0.9589   |
| 0.0709        | 9.0   | 1530 | 0.1640          | 1.0       | 5.4317        | 0.975    | 0.9776   |
| 0.0595        | 10.0  | 1700 | 0.1848          | 1.0       | 5.3818        | 0.9646   | 0.9432   |
| 0.0368        | 11.0  | 1870 | 0.1740          | 1.0       | 5.4152        | 0.9688   | 0.9647   |
| 0.0257        | 12.0  | 2040 | 0.3008          | 1.0       | 5.3703        | 0.9563   | 0.9349   |
| 0.0137        | 13.0  | 2210 | 0.2582          | 1.0       | 5.4157        | 0.9667   | 0.9567   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1