---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: token_fine_tunned_flipkart_2_gl
  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_gl

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: 0.0275
- Precision: 0.9888
- Recall: 0.9900
- F1: 0.9894
- Accuracy: 0.9924

## 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   | 136  | 0.1945          | 0.9023    | 0.9338 | 0.9178 | 0.9331   |
| No log        | 2.0   | 272  | 0.1232          | 0.9469    | 0.9572 | 0.9520 | 0.9658   |
| No log        | 3.0   | 408  | 0.0852          | 0.9595    | 0.9688 | 0.9641 | 0.9747   |
| 0.2214        | 4.0   | 544  | 0.0603          | 0.9723    | 0.9760 | 0.9741 | 0.9831   |
| 0.2214        | 5.0   | 680  | 0.0455          | 0.9770    | 0.9819 | 0.9794 | 0.9865   |
| 0.2214        | 6.0   | 816  | 0.0357          | 0.9823    | 0.9863 | 0.9843 | 0.9887   |
| 0.2214        | 7.0   | 952  | 0.0307          | 0.9869    | 0.9894 | 0.9882 | 0.9916   |
| 0.0938        | 8.0   | 1088 | 0.0275          | 0.9888    | 0.9900 | 0.9894 | 0.9924   |


### Framework versions

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