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

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

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: 0.7409
- Accuracy: 0.6533

## 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: 16
- eval_batch_size: 16
- 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5995        | 1.0   | 14421 | 0.6004          | 0.6644   |
| 0.5859        | 2.0   | 28842 | 0.5985          | 0.6691   |
| 0.5411        | 3.0   | 43263 | 0.6346          | 0.6630   |
| 0.4888        | 4.0   | 57684 | 0.6668          | 0.6591   |
| 0.4483        | 5.0   | 72105 | 0.7409          | 0.6533   |


### Framework versions

- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1