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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-q-classifier-2
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-q-classifier-2
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2779
- Accuracy: 0.9421
- Precision Weighted: 0.9429
- Recall Weighted: 0.9421
- F1 Weighted: 0.9421
- Precision Macro: 0.9429
- Recall Macro: 0.9421
- F1 Macro: 0.9421
## 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
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Weighted | Recall Weighted | F1 Weighted | Precision Macro | Recall Macro | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------------:|:---------------:|:-----------:|:---------------:|:------------:|:--------:|
| No log | 1.0 | 48 | 0.2252 | 0.9144 | 0.9144 | 0.9144 | 0.9144 | 0.9144 | 0.9144 | 0.9144 |
| No log | 2.0 | 96 | 0.1682 | 0.9329 | 0.9333 | 0.9329 | 0.9329 | 0.9333 | 0.9329 | 0.9329 |
| No log | 3.0 | 144 | 0.2251 | 0.9236 | 0.9269 | 0.9236 | 0.9235 | 0.9269 | 0.9236 | 0.9235 |
| No log | 4.0 | 192 | 0.2421 | 0.9352 | 0.9376 | 0.9352 | 0.9351 | 0.9376 | 0.9352 | 0.9351 |
| No log | 5.0 | 240 | 0.2138 | 0.9375 | 0.9383 | 0.9375 | 0.9375 | 0.9383 | 0.9375 | 0.9375 |
| No log | 6.0 | 288 | 0.2165 | 0.9398 | 0.9399 | 0.9398 | 0.9398 | 0.9399 | 0.9398 | 0.9398 |
| No log | 7.0 | 336 | 0.2470 | 0.9398 | 0.9408 | 0.9398 | 0.9398 | 0.9408 | 0.9398 | 0.9398 |
| No log | 8.0 | 384 | 0.2509 | 0.9352 | 0.9353 | 0.9352 | 0.9352 | 0.9353 | 0.9352 | 0.9352 |
| No log | 9.0 | 432 | 0.2686 | 0.9352 | 0.9355 | 0.9352 | 0.9352 | 0.9355 | 0.9352 | 0.9352 |
| No log | 10.0 | 480 | 0.2779 | 0.9421 | 0.9429 | 0.9421 | 0.9421 | 0.9429 | 0.9421 | 0.9421 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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