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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: aift-model-review-multiple-label-classification
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. -->
# aift-model-review-multiple-label-classification
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: 3.0090
- Accuracy Thresh: 0.9179
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Thresh |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|
| No log | 1.0 | 129 | 2.2623 | 0.3531 |
| No log | 2.0 | 258 | 1.6019 | 0.5913 |
| No log | 3.0 | 387 | 1.3774 | 0.7378 |
| 2.6175 | 4.0 | 516 | 1.3383 | 0.7875 |
| 2.6175 | 5.0 | 645 | 1.2456 | 0.8006 |
| 2.6175 | 6.0 | 774 | 1.3044 | 0.8679 |
| 2.6175 | 7.0 | 903 | 1.4123 | 0.8746 |
| 0.7127 | 8.0 | 1032 | 1.5500 | 0.8872 |
| 0.7127 | 9.0 | 1161 | 1.6639 | 0.8894 |
| 0.7127 | 10.0 | 1290 | 1.8716 | 0.9024 |
| 0.7127 | 11.0 | 1419 | 1.8131 | 0.8985 |
| 0.3804 | 12.0 | 1548 | 2.1177 | 0.9059 |
| 0.3804 | 13.0 | 1677 | 2.1873 | 0.9105 |
| 0.3804 | 14.0 | 1806 | 2.3237 | 0.9098 |
| 0.3804 | 15.0 | 1935 | 2.5947 | 0.9112 |
| 0.2297 | 16.0 | 2064 | 2.5776 | 0.9116 |
| 0.2297 | 17.0 | 2193 | 2.7601 | 0.9158 |
| 0.2297 | 18.0 | 2322 | 2.6187 | 0.9165 |
| 0.2297 | 19.0 | 2451 | 2.9175 | 0.9165 |
| 0.1588 | 20.0 | 2580 | 2.9085 | 0.9168 |
| 0.1588 | 21.0 | 2709 | 2.8516 | 0.9183 |
| 0.1588 | 22.0 | 2838 | 2.8932 | 0.9179 |
| 0.1588 | 23.0 | 2967 | 2.8514 | 0.9175 |
| 0.1154 | 24.0 | 3096 | 3.0075 | 0.9179 |
| 0.1154 | 25.0 | 3225 | 3.0090 | 0.9179 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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