---
base_model: /content/model/emotion-classificationV3/checkpoint-60
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: emotion-classificationV3
  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. -->

# emotion-classificationV3

This model is a fine-tuned version of [/content/model/emotion-classificationV3/checkpoint-60](https://huggingface.co//content/model/emotion-classificationV3/checkpoint-60) on FastJobs/Visual_Emotional_Analysis Dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5765
- Accuracy: 0.8438

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

FastJobs/Visual_Emotional_Analysis

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 143
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 0.6923          | 0.7937   |
| 0.5541        | 2.0   | 10   | 0.7871          | 0.8063   |
| 0.5541        | 3.0   | 15   | 0.7193          | 0.8313   |
| 0.5168        | 4.0   | 20   | 0.6446          | 0.825    |
| 0.5168        | 5.0   | 25   | 0.5653          | 0.8438   |
| 0.4627        | 6.0   | 30   | 0.7244          | 0.8063   |
| 0.4627        | 7.0   | 35   | 0.7213          | 0.7937   |
| 0.4516        | 8.0   | 40   | 0.6082          | 0.8313   |
| 0.4516        | 9.0   | 45   | 0.7545          | 0.8063   |
| 0.4339        | 10.0  | 50   | 0.5320          | 0.8562   |
| 0.4339        | 11.0  | 55   | 0.6222          | 0.8187   |
| 0.4233        | 12.0  | 60   | 0.6104          | 0.8438   |
| 0.4233        | 13.0  | 65   | 0.5913          | 0.825    |
| 0.3976        | 14.0  | 70   | 0.6852          | 0.8125   |
| 0.3976        | 15.0  | 75   | 0.6227          | 0.8125   |
| 0.3933        | 16.0  | 80   | 0.5550          | 0.825    |
| 0.3933        | 17.0  | 85   | 0.5438          | 0.8438   |
| 0.4359        | 18.0  | 90   | 0.5916          | 0.825    |
| 0.4359        | 19.0  | 95   | 0.6037          | 0.8063   |
| 0.3589        | 20.0  | 100  | 0.7102          | 0.8125   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3