---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-parse-message
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-parse-message

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: 0.1225
- Accuracy: 0.9681

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0703        | 1.0   | 1172 | 0.1321          | 0.9666   |
| 0.067         | 2.0   | 2344 | 0.1213          | 0.9679   |
| 0.0603        | 3.0   | 3516 | 0.1302          | 0.9674   |
| 0.0596        | 4.0   | 4688 | 0.1215          | 0.9674   |
| 0.0547        | 5.0   | 5860 | 0.1227          | 0.9681   |
| 0.054         | 6.0   | 7032 | 0.1225          | 0.9681   |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1