---
library_name: transformers
license: apache-2.0
base_model: distilroberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mindmate-emotion-classifier
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mindmate-emotion-classifier

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5719
- Accuracy: 0.7976
- F1 Weighted: 0.7962

## 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: 32
- eval_batch_size: 64
- 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_steps: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|
| 0.6452        | 1.0   | 2268 | 0.6177          | 0.7778   | 0.7804      |
| 0.5152        | 2.0   | 4536 | 0.5764          | 0.7867   | 0.7849      |
| 0.4566        | 3.0   | 6804 | 0.5719          | 0.7976   | 0.7962      |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2