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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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