---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
- nlp
- language-model
- sentiment-analysis
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: kritika_distilbert_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# kritika_distilbert_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: 0.5545
- Accuracy: 0.8424
- F1: 0.8424
- Precision: 0.8426
- Recall: 0.8424

## 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 adamw_torch 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     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4212        | 1.0   | 534  | 0.4236          | 0.8189   | 0.8172 | 0.8313    | 0.8189 |
| 0.253         | 2.0   | 1068 | 0.4338          | 0.8443   | 0.8442 | 0.8446    | 0.8443 |
| 0.1618        | 3.0   | 1602 | 0.5545          | 0.8424   | 0.8424 | 0.8426    | 0.8424 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0