---
library_name: transformers
license: apache-2.0
base_model: tashrifmahmud/sentiment_analysis_model
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment_analysis_model_v2
  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. -->

# sentiment_analysis_model_v2

This model is a fine-tuned version of [tashrifmahmud/sentiment_analysis_model](https://huggingface.co/tashrifmahmud/sentiment_analysis_model) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4342
- Accuracy: 0.8443
- Precision: 0.8404
- Recall: 0.8499
- F1: 0.8451

## 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.365         | 1.0   | 534  | 0.3682          | 0.8396   | 0.8267    | 0.8593 | 0.8427 |
| 0.2804        | 2.0   | 1068 | 0.3892          | 0.8452   | 0.8525    | 0.8349 | 0.8436 |
| 0.2301        | 3.0   | 1602 | 0.4342          | 0.8443   | 0.8404    | 0.8499 | 0.8451 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3