---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: WITHINAPPS_NDD-petclinic_test-content-CWAdj
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# WITHINAPPS_NDD-petclinic_test-content-CWAdj

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: 0.0000
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1  | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|
| No log        | 1.0   | 69   | 0.0002          | 1.0      | 1.0 | 1.0       | 1.0    |
| No log        | 2.0   | 138  | 0.0001          | 1.0      | 1.0 | 1.0       | 1.0    |
| No log        | 3.0   | 207  | 0.0001          | 1.0      | 1.0 | 1.0       | 1.0    |
| No log        | 4.0   | 276  | 0.0000          | 1.0      | 1.0 | 1.0       | 1.0    |
| No log        | 5.0   | 345  | 0.0000          | 1.0      | 1.0 | 1.0       | 1.0    |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1