---
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