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---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-squad
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. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.6645
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 125 | 3.7494 |
| No log | 2.0 | 250 | 4.6551 |
| No log | 3.0 | 375 | 4.9969 |
| 0.6094 | 4.0 | 500 | 4.3655 |
| 0.6094 | 5.0 | 625 | 4.9081 |
| 0.6094 | 6.0 | 750 | 4.5831 |
| 0.6094 | 7.0 | 875 | 4.7445 |
| 0.2684 | 8.0 | 1000 | 5.0672 |
| 0.2684 | 9.0 | 1125 | 4.8105 |
| 0.2684 | 10.0 | 1250 | 4.6566 |
| 0.2684 | 11.0 | 1375 | 5.8653 |
| 0.0965 | 12.0 | 1500 | 4.4089 |
| 0.0965 | 13.0 | 1625 | 4.7304 |
| 0.0965 | 14.0 | 1750 | 5.1014 |
| 0.0965 | 15.0 | 1875 | 4.2105 |
| 0.0381 | 16.0 | 2000 | 4.8819 |
| 0.0381 | 17.0 | 2125 | 4.7390 |
| 0.0381 | 18.0 | 2250 | 5.3897 |
| 0.0381 | 19.0 | 2375 | 5.5069 |
| 0.0112 | 20.0 | 2500 | 5.0056 |
| 0.0112 | 21.0 | 2625 | 5.0906 |
| 0.0112 | 22.0 | 2750 | 5.3302 |
| 0.0112 | 23.0 | 2875 | 5.1362 |
| 0.0099 | 24.0 | 3000 | 5.1425 |
| 0.0099 | 25.0 | 3125 | 5.1981 |
| 0.0099 | 26.0 | 3250 | 5.5815 |
| 0.0099 | 27.0 | 3375 | 5.2460 |
| 0.0061 | 28.0 | 3500 | 5.1738 |
| 0.0061 | 29.0 | 3625 | 4.8819 |
| 0.0061 | 30.0 | 3750 | 4.7672 |
| 0.0061 | 31.0 | 3875 | 5.4433 |
| 0.0063 | 32.0 | 4000 | 4.9059 |
| 0.0063 | 33.0 | 4125 | 4.7085 |
| 0.0063 | 34.0 | 4250 | 4.6759 |
| 0.0063 | 35.0 | 4375 | 5.0234 |
| 0.0025 | 36.0 | 4500 | 4.8672 |
| 0.0025 | 37.0 | 4625 | 4.9866 |
| 0.0025 | 38.0 | 4750 | 5.4582 |
| 0.0025 | 39.0 | 4875 | 5.1790 |
| 0.0073 | 40.0 | 5000 | 5.0817 |
| 0.0073 | 41.0 | 5125 | 4.9067 |
| 0.0073 | 42.0 | 5250 | 4.6703 |
| 0.0073 | 43.0 | 5375 | 4.7862 |
| 0.0005 | 44.0 | 5500 | 4.8015 |
| 0.0005 | 45.0 | 5625 | 4.6506 |
| 0.0005 | 46.0 | 5750 | 4.6334 |
| 0.0005 | 47.0 | 5875 | 4.6804 |
| 0.0015 | 48.0 | 6000 | 4.6257 |
| 0.0015 | 49.0 | 6125 | 4.6653 |
| 0.0015 | 50.0 | 6250 | 4.6645 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1
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