---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: token_fine_tunned_flipkart_2
  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. -->

# token_fine_tunned_flipkart_2

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: 0.3435
- Precision: 0.8797
- Recall: 0.9039
- F1: 0.8916
- Accuracy: 0.9061

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 109  | 0.5647          | 0.7398    | 0.8123 | 0.7744 | 0.8111   |
| No log        | 2.0   | 218  | 0.3863          | 0.8165    | 0.8751 | 0.8448 | 0.8716   |
| No log        | 3.0   | 327  | 0.3367          | 0.8599    | 0.8847 | 0.8721 | 0.8869   |
| No log        | 4.0   | 436  | 0.3266          | 0.8688    | 0.8911 | 0.8798 | 0.8977   |
| 0.527         | 5.0   | 545  | 0.3508          | 0.8595    | 0.8898 | 0.8744 | 0.8909   |
| 0.527         | 6.0   | 654  | 0.3410          | 0.8748    | 0.9045 | 0.8894 | 0.9009   |
| 0.527         | 7.0   | 763  | 0.3431          | 0.8754    | 0.9045 | 0.8897 | 0.9049   |
| 0.527         | 8.0   | 872  | 0.3435          | 0.8797    | 0.9039 | 0.8916 | 0.9061   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1