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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: aift-model
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
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: 3.1789
- Accuracy Thresh: 0.9161
## 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 | 2.3568 | 0.3224 |
| No log | 2.0 | 258 | 1.6533 | 0.5518 |
| No log | 3.0 | 387 | 1.3939 | 0.7174 |
| 2.7357 | 4.0 | 516 | 1.3937 | 0.7875 |
| 2.7357 | 5.0 | 645 | 1.3416 | 0.8023 |
| 2.7357 | 6.0 | 774 | 1.3744 | 0.8696 |
| 2.7357 | 7.0 | 903 | 1.4840 | 0.8753 |
| 0.727 | 8.0 | 1032 | 1.6799 | 0.8858 |
| 0.727 | 9.0 | 1161 | 1.6802 | 0.8830 |
| 0.727 | 10.0 | 1290 | 1.8544 | 0.8968 |
| 0.727 | 11.0 | 1419 | 1.8931 | 0.8971 |
| 0.4047 | 12.0 | 1548 | 2.1624 | 0.8978 |
| 0.4047 | 13.0 | 1677 | 2.3448 | 0.9042 |
| 0.4047 | 14.0 | 1806 | 2.4661 | 0.9087 |
| 0.4047 | 15.0 | 1935 | 2.5098 | 0.9087 |
| 0.2396 | 16.0 | 2064 | 2.7352 | 0.9130 |
| 0.2396 | 17.0 | 2193 | 2.7756 | 0.9123 |
| 0.2396 | 18.0 | 2322 | 2.9367 | 0.9151 |
| 0.2396 | 19.0 | 2451 | 2.9757 | 0.9140 |
| 0.1658 | 20.0 | 2580 | 2.9550 | 0.9140 |
| 0.1658 | 21.0 | 2709 | 3.0914 | 0.9161 |
| 0.1658 | 22.0 | 2838 | 3.1505 | 0.9158 |
| 0.1658 | 23.0 | 2967 | 3.0856 | 0.9147 |
| 0.1233 | 24.0 | 3096 | 3.1968 | 0.9175 |
| 0.1233 | 25.0 | 3225 | 3.1789 | 0.9161 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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