---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentiment-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. -->

# sentiment-model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7470
- Accuracy: 0.6598
- F1 Weighted: 0.6493
- F1 Macro: 0.6493

## 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: 32
- eval_batch_size: 32
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|
| 1.0498        | 1.0   | 58   | 0.8737          | 0.6080   | 0.5529      | 0.5529   |
| 0.8304        | 2.0   | 116  | 0.7226          | 0.6975   | 0.6881      | 0.6881   |
| 0.6785        | 3.0   | 174  | 0.7117          | 0.6821   | 0.6736      | 0.6736   |


### Framework versions

- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.23.1