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---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-distilbert-uncased-on-HOPE
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. -->
# finetuned-distilbert-uncased-on-HOPE
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3303
- Accuracy: 0.5429
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4925 | 1.0 | 289 | 1.4588 | 0.5140 |
| 1.2379 | 2.0 | 578 | 1.3627 | 0.5339 |
| 1.0435 | 3.0 | 867 | 1.3433 | 0.5492 |
| 1.1216 | 4.0 | 1156 | 1.3632 | 0.5357 |
| 0.9046 | 5.0 | 1445 | 1.4644 | 0.5086 |
| 0.855 | 6.0 | 1734 | 1.5160 | 0.5185 |
| 0.6505 | 7.0 | 2023 | 1.6085 | 0.5149 |
| 0.5166 | 8.0 | 2312 | 1.6686 | 0.5059 |
| 0.5659 | 9.0 | 2601 | 1.7079 | 0.5032 |
| 0.5263 | 10.0 | 2890 | 1.7293 | 0.5086 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.3.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1
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