---
library_name: transformers
license: mit
base_model: jhu-clsp/mmBERT-base
tags:
- multi_label_classification
- generated_from_trainer
model-index:
- name: finetuned_model_emotion_detection
  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. -->

# finetuned_model_emotion_detection

This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3474
- F1 Macro: 0.5055

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 223  | 0.2843          | 0.4052   |
| No log        | 2.0   | 446  | 0.2643          | 0.4646   |
| 0.2521        | 3.0   | 669  | 0.3474          | 0.5055   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.2.0
- Tokenizers 0.22.1