---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: nouns-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. -->

# nouns-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: 0.6913
- Accuracy: 0.5076
- F1: 0.4327
- Precision: 0.3217
- Recall: 0.6607

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6889        | 1.0   | 50   | 0.6913          | 0.5076   | 0.4327 | 0.3217    | 0.6607 |
| 0.6419        | 2.0   | 100  | 0.6826          | 0.5381   | 0.4204 | 0.3267    | 0.5893 |
| 0.5901        | 3.0   | 150  | 0.6784          | 0.5838   | 0.4225 | 0.3488    | 0.5357 |


### Framework versions

- Transformers 5.12.1
- Pytorch 2.11.0+cpu
- Datasets 4.0.0
- Tokenizers 0.22.2