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

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

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: 2.2439
- Macro F1: 0.3485
- Weighted F1: 0.3644
- Accuracy: 0.3689

## 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: 64
- eval_batch_size: 128
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Weighted F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|
| 2.4474        | 1.0   | 1625 | 2.4144          | 0.2943   | 0.3186      | 0.3269   |
| 2.261         | 2.0   | 3250 | 2.2982          | 0.3330   | 0.3523      | 0.3577   |
| 2.1515        | 3.0   | 4875 | 2.2638          | 0.3393   | 0.3567      | 0.3625   |
| 2.0117        | 4.0   | 6500 | 2.2536          | 0.3456   | 0.3634      | 0.3684   |
| 1.9649        | 5.0   | 8125 | 2.2569          | 0.3443   | 0.3630      | 0.3687   |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.10.0+cu128
- Datasets 2.14.7
- Tokenizers 0.22.2