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---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: ATE
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. -->
# ATE
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: 0.2645
- F1-score: 0.8113
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2839 | 1.0 | 226 | 0.2148 | 0.7160 |
| 0.1153 | 2.0 | 452 | 0.1899 | 0.7830 |
| 0.0677 | 3.0 | 678 | 0.1942 | 0.8008 |
| 0.0456 | 4.0 | 904 | 0.2249 | 0.8012 |
| 0.0393 | 5.0 | 1130 | 0.2361 | 0.8077 |
| 0.027 | 6.0 | 1356 | 0.2455 | 0.8120 |
| 0.0226 | 7.0 | 1582 | 0.2486 | 0.8068 |
| 0.0198 | 8.0 | 1808 | 0.2602 | 0.8156 |
| 0.0171 | 9.0 | 2034 | 0.2640 | 0.8155 |
| 0.0161 | 10.0 | 2260 | 0.2645 | 0.8113 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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